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679 results on '"Schofield PR"'

1. Protein network analysis reveals selectively vulnerable regions and biological processes in FTD

Author: Bonham, Luke W, Steele, Natasha ZR, Karch, Celeste M, Manzoni, Claudia, Geier, Ethan G, Wen, Natalie, Ofori-Kuragu, Aaron, Momeni, Parastoo, Hardy, John, Miller, Zachary A, Hess, Christopher P, Lewis, Patrick, Miller, Bruce L, Seeley, William W, Baranzini, Sergio E, Desikan, Rahul S, Ferrari, Raffaele, Yokoyama, Jennifer S, Ferrari, R, Hernandez, DG, Nalls, MA, Rohrer, JD, Ramasamy, A, Kwok, JBJ, Dobson-Stone, C, Schofield, PR, Halliday, GM, Hodges, JR, Piguet, O, Bartley, L, Thompson, E, Hernández, I, Ruiz, A, Boada, M, Borroni, B, Padovani, A, Cruchaga, C, Cairns, NJ, Benussi, L, Binetti, G, Ghidoni, R, Forloni, G, Albani, D, Galimberti, D, Fenoglio, C, Serpente, M, Scarpini, E, Clarimón, J, Lleó, A, Blesa, R, Waldö, M Landqvist, Nilsson, K, Nilsson, C, Mackenzie, IRA, Hsiung, G-YR, Mann, D, Grafman, J, Morris, CM, Attems, J, Griffiths, TD, McKeith, IG, Thomas, AJ, Pietrini, P, Huey, ED, Wassermann, EM, Baborie, A, Jaros, E, Tierney, MC, Pastor, P, Razquin, C, Ortega-Cubero, S, Alonso, E, Perneczky, R, Diehl-Schmid, J, Alexopoulos, P, Kurz, A, Rainero, I, Rubino, E, Pinessi, L, Rogaeva, E, St George-Hyslop, P, Rossi, G, Tagliavini, F, Giaccone, G, Rowe, JB, Schlachetzki, JCM, Uphill, J, Collinge, J, Mead, S, Danek, A, Van Deerlin, VM, Grossman, M, Trojanowski, JQ, van der Zee, J, Van Broeckhoven, C, Cappa, SF, Leber, I, Hannequin, D, and Golfier, V
Subjects: Biological Sciences, Bioinformatics and Computational Biology, Genetics, Aging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer's Disease Related Dementias (ADRD), Frontotemporal Dementia (FTD), Acquired Cognitive Impairment, Dementia, Biotechnology, Neurodegenerative, Rare Diseases, Neurosciences, Brain Disorders, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Neurological, International FTD-Genomics Consortium, Clinical sciences
Abstract: ObjectiveThe neuroanatomical profile of behavioral variant frontotemporal dementia (bvFTD) suggests a common biological etiology of disease despite disparate pathologic causes; we investigated the genetic underpinnings of this selective regional vulnerability to identify new risk factors for bvFTD.MethodsWe used recently developed analytical techniques designed to address the limitations of genome-wide association studies to generate a protein interaction network of 63 bvFTD risk genes. We characterized this network using gene expression data from healthy and diseased human brain tissue, evaluating regional network expression patterns across the lifespan as well as the cell types and biological processes most affected in bvFTD.ResultsWe found that bvFTD network genes show enriched expression across the human lifespan in vulnerable neuronal populations, are implicated in cell signaling, cell cycle, immune function, and development, and are differentially expressed in pathologically confirmed frontotemporal lobar degeneration cases. Five of the genes highlighted by our differential expression analyses, BAIAP2, ERBB3, POU2F2, SMARCA2, and CDC37, appear to be novel bvFTD risk loci.ConclusionsOur findings suggest that the cumulative burden of common genetic variation in an interacting protein network expressed in specific brain regions across the lifespan may influence susceptibility to bvFTD.
Published: 2018

2. Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Author: McWhinney, SR, Hlinka, J, Bakstein, E, Dietze, LMF, Corkum, ELV, Abé, C, Alda, M, Alexander, N, Benedetti, F, Berk, M, Bøen, E, Bonnekoh, LM, Boye, B, Brosch, K, Canales-Rodríguez, EJ, Cannon, DM, Dannlowski, U, Demro, C, Diaz-Zuluaga, A, Elvsåshagen, T, Eyler, LT, Fortea, L, Fullerton, JM, Goltermann, J, Gotlib, IH, Grotegerd, D, Haarman, B, Hahn, T, Howells, FM, Jamalabadi, H, Jansen, A, Kircher, T, Klahn, AL, Kuplicki, R, Lahud, E, Landén, M, Leehr, EJ, Lopez-Jaramillo, C, Mackey, S, Malt, U, Martyn, F, Mazza, E, McDonald, C, McPhilemy, G, Meier, S, Meinert, S, Melloni, E, Mitchell, PB, Nabulsi, L, Nenadić, I, Nitsch, R, Opel, N, Ophoff, RA, Ortuño, M, Overs, BJ, Pineda-Zapata, J, Pomarol-Clotet, E, Radua, J, Repple, J, Roberts, G, Rodriguez-Cano, E, Sacchet, MD, Salvador, R, Savitz, J, Scheffler, F, Schofield, PR, Schürmeyer, N, Shen, C, Sim, K, Sponheim, SR, Stein, DJ, Stein, F, Straube, B, Suo, C, Temmingh, H, Teutenberg, L, Thomas-Odenthal, F, Thomopoulos, SI, Urosevic, S, Usemann, P, van Haren, NEM, Vargas, C, Vieta, E, Vilajosana, E, Vreeker, A, Winter, NR, Yatham, LN, Thompson, PM, Andreassen, OA, Ching, CRK, Hajek, T, McWhinney, SR, Hlinka, J, Bakstein, E, Dietze, LMF, Corkum, ELV, Abé, C, Alda, M, Alexander, N, Benedetti, F, Berk, M, Bøen, E, Bonnekoh, LM, Boye, B, Brosch, K, Canales-Rodríguez, EJ, Cannon, DM, Dannlowski, U, Demro, C, Diaz-Zuluaga, A, Elvsåshagen, T, Eyler, LT, Fortea, L, Fullerton, JM, Goltermann, J, Gotlib, IH, Grotegerd, D, Haarman, B, Hahn, T, Howells, FM, Jamalabadi, H, Jansen, A, Kircher, T, Klahn, AL, Kuplicki, R, Lahud, E, Landén, M, Leehr, EJ, Lopez-Jaramillo, C, Mackey, S, Malt, U, Martyn, F, Mazza, E, McDonald, C, McPhilemy, G, Meier, S, Meinert, S, Melloni, E, Mitchell, PB, Nabulsi, L, Nenadić, I, Nitsch, R, Opel, N, Ophoff, RA, Ortuño, M, Overs, BJ, Pineda-Zapata, J, Pomarol-Clotet, E, Radua, J, Repple, J, Roberts, G, Rodriguez-Cano, E, Sacchet, MD, Salvador, R, Savitz, J, Scheffler, F, Schofield, PR, Schürmeyer, N, Shen, C, Sim, K, Sponheim, SR, Stein, DJ, Stein, F, Straube, B, Suo, C, Temmingh, H, Teutenberg, L, Thomas-Odenthal, F, Thomopoulos, SI, Urosevic, S, Usemann, P, van Haren, NEM, Vargas, C, Vieta, E, Vilajosana, E, Vreeker, A, Winter, NR, Yatham, LN, Thompson, PM, Andreassen, OA, Ching, CRK, and Hajek, T
Abstract: Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associati
Published: 2024

3. Polygenic Scores and Onset of Major Mood or Psychotic Disorders Among Offspring of Affected Parents

Author: Zwicker, A, Fullerton, JM, Mullins, N, Rice, F, Hafeman, DM, van Haren, NEM, Setiaman, N, Merranko, JA, Goldstein, BI, Ferrera, AG, Stapp, EK, de la Serna, E, Moreno, D, Sugranyes, G, Herrero, SM, Roberts, G, Toma, C, Schofield, PR, Edenberg, HJ, Wilcox, HC, McInnis, MG, Powell, V, Propper, L, Denovan-Wright, E, Rouleau, G, Castro-Fornieles, J, Hillegers, MHJ, Birmaher, B, Thapar, A, Mitchell, PB, Lewis, CM, Alda, M, Nurnberger, JI, Uher, R, Zwicker, A, Fullerton, JM, Mullins, N, Rice, F, Hafeman, DM, van Haren, NEM, Setiaman, N, Merranko, JA, Goldstein, BI, Ferrera, AG, Stapp, EK, de la Serna, E, Moreno, D, Sugranyes, G, Herrero, SM, Roberts, G, Toma, C, Schofield, PR, Edenberg, HJ, Wilcox, HC, McInnis, MG, Powell, V, Propper, L, Denovan-Wright, E, Rouleau, G, Castro-Fornieles, J, Hillegers, MHJ, Birmaher, B, Thapar, A, Mitchell, PB, Lewis, CM, Alda, M, Nurnberger, JI, and Uher, R
Published: 2023

4. Tackling Dementia Together via The Australian Dementia Network (ADNeT): A Summary of Initiatives, Progress and Plans.

Author: Naismith, SL, Michaelian, JC, Santos, C, Mehrani, I, Robertson, J, Wallis, K, Lin, X, Ward, SA, Martins, R, Masters, CL, Breakspear, M, Ahern, S, Fripp, J, Schofield, PR, Sachdev, PS, Rowe, CC, Naismith, SL, Michaelian, JC, Santos, C, Mehrani, I, Robertson, J, Wallis, K, Lin, X, Ward, SA, Martins, R, Masters, CL, Breakspear, M, Ahern, S, Fripp, J, Schofield, PR, Sachdev, PS, and Rowe, CC
Abstract: In 2018, the Australian Dementia Network (ADNeT) was established to bring together Australia's leading dementia researchers, people with living experience and clinicians to transform research and clinical care in the field. To address dementia diagnosis, treatment, and care, ADNeT has established three core initiatives: the Clinical Quality Registry (CQR), Memory Clinics, and Screening for Trials. Collectively, the initiatives have developed an integrated clinical and research community, driving practice excellence in this field, leading to novel innovations in diagnostics, clinical care, professional development, quality and harmonization of healthcare, clinical trials, and translation of research into practice. Australia now has a national Registry for Mild Cognitive Impairment and dementia with 55 participating clinical sites, an extensive map of memory clinic services, national Memory and Cognition Clinic Guidelines and specialized screening for trials sites in five states. This paper provides an overview of ADNeT's achievements to date and future directions. With the increase in dementia cases expected over coming decades, and with recent advances in plasma biomarkers and amyloid lowering therapies, the nationally coordinated initiatives and partnerships ADNeT has established are critical for increased national prevention efforts, co-ordinated implementation of emerging treatments for Alzheimer's disease, innovation of early and accurate diagnosis, driving continuous improvements in clinical care and patient outcome and access to post-diagnostic support and clinical trials. For a heterogenous disorder such as dementia, which is now the second leading cause of death in Australia following cardiovascular disease, the case for adequate investment into research and development has grown even more compelling.
Published: 2023

5. Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN).

Author: McKay, NS, Gordon, BA, Hornbeck, RC, Dincer, A, Flores, S, Keefe, SJ, Joseph-Mathurin, N, Jack, CR, Koeppe, R, Millar, PR, Ances, BM, Chen, CD, Daniels, A, Hobbs, DA, Jackson, K, Koudelis, D, Massoumzadeh, P, McCullough, A, Nickels, ML, Rahmani, F, Swisher, L, Wang, Q, Allegri, RF, Berman, SB, Brickman, AM, Brooks, WS, Cash, DM, Chhatwal, JP, Day, GS, Farlow, MR, la Fougère, C, Fox, NC, Fulham, M, Ghetti, B, Graff-Radford, N, Ikeuchi, T, Klunk, W, Lee, J-H, Levin, J, Martins, R, Masters, CL, McConathy, J, Mori, H, Noble, JM, Reischl, G, Rowe, C, Salloway, S, Sanchez-Valle, R, Schofield, PR, Shimada, H, Shoji, M, Su, Y, Suzuki, K, Vöglein, J, Yakushev, I, Cruchaga, C, Hassenstab, J, Karch, C, McDade, E, Perrin, RJ, Xiong, C, Morris, JC, Bateman, RJ, Benzinger, TLS, Dominantly Inherited Alzheimer Network, McKay, NS, Gordon, BA, Hornbeck, RC, Dincer, A, Flores, S, Keefe, SJ, Joseph-Mathurin, N, Jack, CR, Koeppe, R, Millar, PR, Ances, BM, Chen, CD, Daniels, A, Hobbs, DA, Jackson, K, Koudelis, D, Massoumzadeh, P, McCullough, A, Nickels, ML, Rahmani, F, Swisher, L, Wang, Q, Allegri, RF, Berman, SB, Brickman, AM, Brooks, WS, Cash, DM, Chhatwal, JP, Day, GS, Farlow, MR, la Fougère, C, Fox, NC, Fulham, M, Ghetti, B, Graff-Radford, N, Ikeuchi, T, Klunk, W, Lee, J-H, Levin, J, Martins, R, Masters, CL, McConathy, J, Mori, H, Noble, JM, Reischl, G, Rowe, C, Salloway, S, Sanchez-Valle, R, Schofield, PR, Shimada, H, Shoji, M, Su, Y, Suzuki, K, Vöglein, J, Yakushev, I, Cruchaga, C, Hassenstab, J, Karch, C, McDade, E, Perrin, RJ, Xiong, C, Morris, JC, Bateman, RJ, Benzinger, TLS, and Dominantly Inherited Alzheimer Network
Abstract: The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual's point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of 'sporadic' AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers.
Published: 2023

6. Patterns and implications of neurological examination findings in autosomal dominant Alzheimer disease

Author: Voeglein, J, Franzmeier, N, Morris, JC, Dieterich, M, McDade, E, Simons, M, Preische, O, Hofmann, A, Hassenstab, J, Benzinger, TL, Fagan, A, Noble, JM, Berman, SB, Graff-Radford, NR, Ghetti, B, Farlow, MR, Chhatwal, JP, Salloway, S, Xiong, C, Karch, CM, Cairns, N, Perrin, RJ, Day, G, Martins, R, Sanchez-Valle, R, Mori, H, Shimada, H, Ikeuchi, T, Suzuki, K, Schofield, PR, Masters, CL, Goate, A, Buckles, V, Fox, NC, Chrem, P, Allegri, R, Ringman, JM, Yakushev, I, Laske, C, Jucker, M, Hoglinger, G, Bateman, RJ, Danek, A, Levin, J, Voeglein, J, Franzmeier, N, Morris, JC, Dieterich, M, McDade, E, Simons, M, Preische, O, Hofmann, A, Hassenstab, J, Benzinger, TL, Fagan, A, Noble, JM, Berman, SB, Graff-Radford, NR, Ghetti, B, Farlow, MR, Chhatwal, JP, Salloway, S, Xiong, C, Karch, CM, Cairns, N, Perrin, RJ, Day, G, Martins, R, Sanchez-Valle, R, Mori, H, Shimada, H, Ikeuchi, T, Suzuki, K, Schofield, PR, Masters, CL, Goate, A, Buckles, V, Fox, NC, Chrem, P, Allegri, R, Ringman, JM, Yakushev, I, Laske, C, Jucker, M, Hoglinger, G, Bateman, RJ, Danek, A, and Levin, J
Abstract: INTRODUCTION: As knowledge about neurological examination findings in autosomal dominant Alzheimer disease (ADAD) is incomplete, we aimed to determine the frequency and significance of neurological examination findings in ADAD. METHODS: Frequencies of neurological examination findings were compared between symptomatic mutation carriers and non mutation carriers from the Dominantly Inherited Alzheimer Network (DIAN) to define AD neurological examination findings. AD neurological examination findings were analyzed regarding frequency, association with and predictive value regarding cognitive decline, and association with brain atrophy in symptomatic mutation carriers. RESULTS: AD neurological examination findings included abnormal deep tendon reflexes, gait disturbance, pathological cranial nerve examination findings, tremor, abnormal finger to nose and heel to shin testing, and compromised motor strength. The frequency of AD neurological examination findings was 65.1%. Cross-sectionally, mutation carriers with AD neurological examination findings showed a more than two-fold faster cognitive decline and had greater parieto-temporal atrophy, including hippocampal atrophy. Longitudinally, AD neurological examination findings predicted a significantly greater decline over time. DISCUSSION: ADAD features a distinct pattern of neurological examination findings that is useful to estimate prognosis and may inform clinical care and therapeutic trial designs.
Published: 2023

7. High polygenic risk score for exceptional longevity is associated with a healthy metabolic profile

Author: Revelas, M, Thalamuthu, A, Zettergren, A, Oldmeadow, C, Najar, J, Seidu, NM, Armstrong, NJ, Riveros, C, Kwok, JB, Schofield, PR, Trollor, JN, Waern, M, Wright, MJ, Zetterberg, H, Ames, D, Belnnow, K, Brodaty, H, Scott, RJ, Skoog, I, Attia, JR, Sachdev, PS, Mather, KA, Revelas, M, Thalamuthu, A, Zettergren, A, Oldmeadow, C, Najar, J, Seidu, NM, Armstrong, NJ, Riveros, C, Kwok, JB, Schofield, PR, Trollor, JN, Waern, M, Wright, MJ, Zetterberg, H, Ames, D, Belnnow, K, Brodaty, H, Scott, RJ, Skoog, I, Attia, JR, Sachdev, PS, and Mather, KA
Abstract: Healthy metabolic measures in humans are associated with longevity. Dysregulation leads to metabolic syndrome (MetS) and negative health outcomes. Recent exceptional longevity (EL) genome wide association studies have facilitated estimation of an individual's polygenic risk score (PRS) for EL. We tested the hypothesis that individuals with high ELPRS have a low prevalence of MetS. Participants were from five cohorts of middle-aged to older adults. The primary analyses were performed in the UK Biobank (UKBB) (n = 407,800, 40-69 years). Replication analyses were undertaken using three Australian studies: Hunter Community Study (n = 2122, 55-85 years), Older Australian Twins Study (n = 539, 65-90 years) and Sydney Memory and Ageing Study (n = 925, 70-90 years), as well as the Swedish Gothenburg H70 Birth Cohort Studies (n = 2273, 70-93 years). MetS was defined using established criteria. Regressions and meta-analyses were performed with the ELPRS and MetS and its components. Generally, MetS prevalence (22-30%) was higher in the older cohorts. In the UKBB, high EL polygenic risk was associated with lower MetS prevalence (OR = 0.94, p = 1.84 × 10-42) and its components (p < 2.30 × 10-8). Meta-analyses of the replication cohorts showed nominal associations with MetS (p = 0.028) and 3 MetS components (p < 0.05). This work suggests individuals with a high polygenic risk for EL have a healthy metabolic profile promoting longevity.
Published: 2023

8. Biomarker clustering in autosomal dominant Alzheimer's disease

Author: Luckett, PH, Chen, C, Gordon, BA, Wisch, J, Berman, SB, Chhatwal, JP, Cruchaga, C, Fagan, AM, Farlow, MR, Fox, NC, Jucker, M, Levin, J, Masters, CL, Mori, H, Noble, JM, Salloway, S, Schofield, PR, Brickman, AM, Brooks, WS, Cash, DM, Fulham, MJ, Ghetti, B, Jack, CR, Voeglein, J, Klunk, WE, Koeppe, R, Su, Y, Weiner, M, Wang, Q, Marcus, D, Koudelis, D, Joseph-Mathurin, N, Cash, L, Hornbeck, R, Xiong, C, Perrin, RJ, Karch, CM, Hassenstab, J, McDade, E, Morris, JC, Benzinger, TLS, Bateman, RJ, Ances, BM, Luckett, PH, Chen, C, Gordon, BA, Wisch, J, Berman, SB, Chhatwal, JP, Cruchaga, C, Fagan, AM, Farlow, MR, Fox, NC, Jucker, M, Levin, J, Masters, CL, Mori, H, Noble, JM, Salloway, S, Schofield, PR, Brickman, AM, Brooks, WS, Cash, DM, Fulham, MJ, Ghetti, B, Jack, CR, Voeglein, J, Klunk, WE, Koeppe, R, Su, Y, Weiner, M, Wang, Q, Marcus, D, Koudelis, D, Joseph-Mathurin, N, Cash, L, Hornbeck, R, Xiong, C, Perrin, RJ, Karch, CM, Hassenstab, J, McDade, E, Morris, JC, Benzinger, TLS, Bateman, RJ, and Ances, BM
Abstract: INTRODUCTION: As the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others. METHODS: We used hierarchical clustering to group 19 cross-sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation. RESULTS: Three primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors. DISCUSSION: These results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression.
Published: 2023

9. Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Author: Mullins, N, Kang, J, Campos, A, Coleman, JR, Edwards, AC, Galfalvy, H, Levey, DF, Lori, A, Shabalin, A, Starnawska, A, Su, M-H, Watson, HJ, Adams, M, Awasthi, S, Ganda, M, Hafferty, JD, Hishimoto, A, Kim, M, Okazaki, S, Otsuka, I, Ripke, S, Ware, EB, Bergen, AW, Berrettini, WH, Bohus, M, Brandt, H, Chang, X, Chen, WJ, Chen, H-C, Crawford, S, Crow, S, DiBlasi, E, Duriez, P, Fernandez-Aranda, F, Fichter, MM, Gallinger, S, Glatt, SJ, Gorwood, P, Guo, Y, Hakonarson, H, Halmi, KA, Hwu, H-G, Jain, S, Jamain, S, Jimenez-Murcia, S, Johnson, C, Kaplan, AS, Kaye, WH, Keel, PK, Kennedy, JL, Klump, KL, Li, D, Liao, S-C, Lieb, K, Lilenfeld, L, Liu, C-M, Magistretti, PJ, Marshall, CR, Mitchell, JE, Monson, ET, Myers, RM, Pinto, D, Powers, A, Ramoz, N, Roepke, S, Rozanov, V, Scherer, SW, Schmahl, C, Sokolowski, M, Strober, M, Thornton, LM, Treasure, J, Tsuang, MT, Witt, SH, Woodside, DB, Yilmaz, Z, Zillich, L, Adolfsson, R, Agartz, I, Air, TM, Alda, M, Alfredsson, L, Andreassen, OA, Anjorin, A, Appadurai, V, Artigas, MS, Van der Auwera, S, Azevedo, MH, Bass, N, Bau, CHD, Baune, BT, Bellivier, F, Berger, K, Biernacka, JM, Bigdeli, TB, Binder, EB, Boehnke, M, Boks, MP, Bosch, R, Braff, DL, Bryant, R, Budde, M, Byrne, EM, Cahn, W, Casas, M, Castelao, E, Cervilla, JA, Chaumette, B, Cichon, S, Corvin, A, Craddock, N, Craig, D, Degenhardt, F, Djurovic, S, Edenberg, HJ, Fanous, AH, Foo, JC, Forstner, AJ, Frye, M, Fullerton, JM, Gatt, JM, Gejman, P, Giegling, I, Grabe, HJ, Green, MJ, Grevet, EH, Grigoroiu-Serbanescu, M, Gutierrez, B, Guzman-Parra, J, Hamilton, SP, Hamshere, ML, Hartmann, A, Hauser, J, Heilmann-Heimbach, S, Hoffmann, P, Ising, M, Jones, I, Jones, LA, Jonsson, L, Kahn, RS, Kelsoe, JR, Kendler, KS, Kloiber, S, Koenen, KC, Kogevinas, M, Konte, B, Krebs, M-O, Lander, M, Lawrence, J, Leboyer, M, Lee, PH, Levinson, DF, Liao, C, Lissowska, J, Lucae, S, Mayoral, F, McElroy, SL, McGrath, P, McGuffin, P, McQuillin, A, Medland, SE, Mehta, D, Melle, I, Milaneschi, Y, Mitchell, PB, Molina, E, Morken, G, Mortensen, PB, Mueller-Myhsok, B, Nievergelt, C, Nimgaonkar, V, Noethen, MM, O'Donovan, MC, Ophoff, RA, Owen, MJ, Pato, C, Pato, MT, Penninx, BWJH, Pimm, J, Pistis, G, Potash, JB, Power, RA, Preisig, M, Quested, D, Ramos-Quiroga, JA, Reif, A, Ribases, M, Richarte, V, Rietschel, M, Rivera, M, Roberts, A, Roberts, G, Rouleau, GA, Rovaris, DL, Rujescu, D, Sanchez-Mora, C, Sanders, AR, Schofield, PR, Schulze, TG, Scott, LJ, Serretti, A, Shi, J, Shyn, S, Sirignano, L, Sklar, P, Smeland, OB, Smoller, JW, Sonuga-Barke, EJS, Spalletta, G, Strauss, JS, Swiatkowska, B, Trzaskowski, M, Turecki, G, Vilar-Ribo, L, Vincent, JB, Voelzke, H, Walters, JTR, Weickert, CS, Weickert, TW, Weissman, MM, Williams, LM, Wray, NR, Zai, CC, Ashley-Koch, AE, Beckham, JC, Hauser, ER, Hauser, MA, Kimbrel, NA, Lindquist, JH, McMahon, B, Oslin, DW, Qin, X, Agerbo, E, Borglum, AD, Breen, G, Erlangsen, A, Esko, T, Gelernter, J, Hougaard, DM, Kessler, RC, Kranzler, HR, Li, QS, Martin, NG, McIntosh, AM, Mors, O, Nordentoft, M, Olsen, CM, Porteous, D, Ursano, RJ, Wasserman, D, Werge, T, Whiteman, DC, Bulik, CM, Coon, H, Demontis, D, Docherty, AR, Kuo, P-H, Lewis, CM, Mann, JJ, Renteria, ME, Smith, DJ, Stahl, EA, Stein, MB, Streit, F, Willour, V, Ruderfer, DM, Mullins, N, Kang, J, Campos, A, Coleman, JR, Edwards, AC, Galfalvy, H, Levey, DF, Lori, A, Shabalin, A, Starnawska, A, Su, M-H, Watson, HJ, Adams, M, Awasthi, S, Ganda, M, Hafferty, JD, Hishimoto, A, Kim, M, Okazaki, S, Otsuka, I, Ripke, S, Ware, EB, Bergen, AW, Berrettini, WH, Bohus, M, Brandt, H, Chang, X, Chen, WJ, Chen, H-C, Crawford, S, Crow, S, DiBlasi, E, Duriez, P, Fernandez-Aranda, F, Fichter, MM, Gallinger, S, Glatt, SJ, Gorwood, P, Guo, Y, Hakonarson, H, Halmi, KA, Hwu, H-G, Jain, S, Jamain, S, Jimenez-Murcia, S, Johnson, C, Kaplan, AS, Kaye, WH, Keel, PK, Kennedy, JL, Klump, KL, Li, D, Liao, S-C, Lieb, K, Lilenfeld, L, Liu, C-M, Magistretti, PJ, Marshall, CR, Mitchell, JE, Monson, ET, Myers, RM, Pinto, D, Powers, A, Ramoz, N, Roepke, S, Rozanov, V, Scherer, SW, Schmahl, C, Sokolowski, M, Strober, M, Thornton, LM, Treasure, J, Tsuang, MT, Witt, SH, Woodside, DB, Yilmaz, Z, Zillich, L, Adolfsson, R, Agartz, I, Air, TM, Alda, M, Alfredsson, L, Andreassen, OA, Anjorin, A, Appadurai, V, Artigas, MS, Van der Auwera, S, Azevedo, MH, Bass, N, Bau, CHD, Baune, BT, Bellivier, F, Berger, K, Biernacka, JM, Bigdeli, TB, Binder, EB, Boehnke, M, Boks, MP, Bosch, R, Braff, DL, Bryant, R, Budde, M, Byrne, EM, Cahn, W, Casas, M, Castelao, E, Cervilla, JA, Chaumette, B, Cichon, S, Corvin, A, Craddock, N, Craig, D, Degenhardt, F, Djurovic, S, Edenberg, HJ, Fanous, AH, Foo, JC, Forstner, AJ, Frye, M, Fullerton, JM, Gatt, JM, Gejman, P, Giegling, I, Grabe, HJ, Green, MJ, Grevet, EH, Grigoroiu-Serbanescu, M, Gutierrez, B, Guzman-Parra, J, Hamilton, SP, Hamshere, ML, Hartmann, A, Hauser, J, Heilmann-Heimbach, S, Hoffmann, P, Ising, M, Jones, I, Jones, LA, Jonsson, L, Kahn, RS, Kelsoe, JR, Kendler, KS, Kloiber, S, Koenen, KC, Kogevinas, M, Konte, B, Krebs, M-O, Lander, M, Lawrence, J, Leboyer, M, Lee, PH, Levinson, DF, Liao, C, Lissowska, J, Lucae, S, Mayoral, F, McElroy, SL, McGrath, P, McGuffin, P, McQuillin, A, Medland, SE, Mehta, D, Melle, I, Milaneschi, Y, Mitchell, PB, Molina, E, Morken, G, Mortensen, PB, Mueller-Myhsok, B, Nievergelt, C, Nimgaonkar, V, Noethen, MM, O'Donovan, MC, Ophoff, RA, Owen, MJ, Pato, C, Pato, MT, Penninx, BWJH, Pimm, J, Pistis, G, Potash, JB, Power, RA, Preisig, M, Quested, D, Ramos-Quiroga, JA, Reif, A, Ribases, M, Richarte, V, Rietschel, M, Rivera, M, Roberts, A, Roberts, G, Rouleau, GA, Rovaris, DL, Rujescu, D, Sanchez-Mora, C, Sanders, AR, Schofield, PR, Schulze, TG, Scott, LJ, Serretti, A, Shi, J, Shyn, S, Sirignano, L, Sklar, P, Smeland, OB, Smoller, JW, Sonuga-Barke, EJS, Spalletta, G, Strauss, JS, Swiatkowska, B, Trzaskowski, M, Turecki, G, Vilar-Ribo, L, Vincent, JB, Voelzke, H, Walters, JTR, Weickert, CS, Weickert, TW, Weissman, MM, Williams, LM, Wray, NR, Zai, CC, Ashley-Koch, AE, Beckham, JC, Hauser, ER, Hauser, MA, Kimbrel, NA, Lindquist, JH, McMahon, B, Oslin, DW, Qin, X, Agerbo, E, Borglum, AD, Breen, G, Erlangsen, A, Esko, T, Gelernter, J, Hougaard, DM, Kessler, RC, Kranzler, HR, Li, QS, Martin, NG, McIntosh, AM, Mors, O, Nordentoft, M, Olsen, CM, Porteous, D, Ursano, RJ, Wasserman, D, Werge, T, Whiteman, DC, Bulik, CM, Coon, H, Demontis, D, Docherty, AR, Kuo, P-H, Lewis, CM, Mann, JJ, Renteria, ME, Smith, DJ, Stahl, EA, Stein, MB, Streit, F, Willour, V, and Ruderfer, DM
Abstract: BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.
Published: 2022

10. Genetic variants associated with longitudinal changes in brain structure across the lifespan

Author: Brouwer, RM, Klein, M, Grasby, KL, Schnack, HG, Jahanshad, N, Teeuw, J, Thomopoulos, SI, Sprooten, E, Franz, CE, Gogtay, N, Kremen, WS, Panizzon, MS, Olde Loohuis, LM, Whelan, CD, Aghajani, M, Alloza, C, Alanaes, D, Artiges, E, Ayesa-Arriola, R, Barker, GJ, Bastin, ME, Blok, E, Boen, E, Breukelaar, IA, Bright, JK, Buimer, EEL, Bulow, R, Cannon, DM, Ciufolini, S, Crossley, NA, Damatac, CG, Dazzan, P, de Mol, CL, de Zwarte, SMC, Desrivieres, S, Diaz-Caneja, CM, Doan, NT, Dohm, K, Froehner, JH, Goltermann, J, Grigis, A, Grotegerd, D, Han, LKM, Harris, MA, Hartman, CA, Heany, SJ, Heindel, W, Heslenfeld, DJ, Hohmann, S, Ittermann, B, Jansen, PR, Janssen, J, Jia, T, Jiang, J, Jockwitz, C, Karali, T, Keeser, D, Koevoets, MGJC, Lenroot, RK, Malchow, B, Mandl, RCW, Medel, V, Meinert, S, Morgan, CA, Muehleisen, TW, Nabulsi, L, Opel, N, de la Foz, VO-G, Overs, BJ, Paillere Martinot, M-L, Redlich, R, Marques, TR, Repple, J, Roberts, G, Roshchupkin, GV, Setiaman, N, Shumskaya, E, Stein, F, Sudre, G, Takahashi, S, Thalamuthu, A, Tordesillas-Gutierrez, D, van der Lugt, A, van Haren, NEM, Wardlaw, JM, Wen, W, Westeneng, H-J, Wittfeld, K, Zhu, AH, Zugman, A, Armstrong, NJ, Bonfiglio, G, Bralten, J, Dalvie, S, Davies, G, Di Forti, M, Ding, L, Donohoe, G, Forstner, AJ, Gonzalez-Penas, J, Guimaraes, JPOFT, Homuth, G, Hottenga, J-J, Knol, MJ, Kwok, JBJ, Le Hellard, S, Mather, KA, Milaneschi, Y, Morris, DW, Noethen, MM, Papiol, S, Rietschel, M, Santoro, ML, Steen, VM, Stein, JL, Streit, F, Tankard, RM, Teumer, A, van 't Ent, D, van der Meer, D, van Eijk, KR, Vassos, E, Vazquez-Bourgon, J, Witt, SH, Adams, HHH, Agartz, I, Ames, D, Amunts, K, Andreassen, OA, Arango, C, Banaschewski, T, Baune, BT, Belangero, SI, Bokde, ALW, Boomsma, DI, Bressan, RA, Brodaty, H, Buitelaar, JK, Cahn, W, Caspers, S, Cichon, S, Crespo-Facorro, B, Cox, SR, Dannlowski, U, Elvsashagen, T, Espeseth, T, Falkai, PG, Fisher, SE, Flor, H, Fullerton, JM, Garavan, H, Gowland, PA, Grabe, HJ, Hahn, T, Heinz, A, Hillegers, M, Hoare, J, Hoekstra, PJ, Ikram, MA, Jackowski, AP, Jansen, A, Jonsson, EG, Kahn, RS, Kircher, T, Korgaonkar, MS, Krug, A, Lemaitre, H, Malt, UF, Martinot, J-L, McDonald, C, Mitchell, PB, Muetzel, RL, Murray, RM, Nees, F, Nenadic, I, Oosterlaan, J, Ophoff, RA, Pan, PM, Penninx, BWJH, Poustka, L, Sachdev, PS, Salum, GA, Schofield, PR, Schumann, G, Shaw, P, Sim, K, Smolka, MN, Stein, DJ, Trollor, JN, van den Berg, LH, Veldink, JH, Walter, H, Westlye, LT, Whelan, R, White, T, Wright, MJ, Medland, SE, Franke, B, Thompson, PM, Hulshoff Pol, HE, Brouwer, RM, Klein, M, Grasby, KL, Schnack, HG, Jahanshad, N, Teeuw, J, Thomopoulos, SI, Sprooten, E, Franz, CE, Gogtay, N, Kremen, WS, Panizzon, MS, Olde Loohuis, LM, Whelan, CD, Aghajani, M, Alloza, C, Alanaes, D, Artiges, E, Ayesa-Arriola, R, Barker, GJ, Bastin, ME, Blok, E, Boen, E, Breukelaar, IA, Bright, JK, Buimer, EEL, Bulow, R, Cannon, DM, Ciufolini, S, Crossley, NA, Damatac, CG, Dazzan, P, de Mol, CL, de Zwarte, SMC, Desrivieres, S, Diaz-Caneja, CM, Doan, NT, Dohm, K, Froehner, JH, Goltermann, J, Grigis, A, Grotegerd, D, Han, LKM, Harris, MA, Hartman, CA, Heany, SJ, Heindel, W, Heslenfeld, DJ, Hohmann, S, Ittermann, B, Jansen, PR, Janssen, J, Jia, T, Jiang, J, Jockwitz, C, Karali, T, Keeser, D, Koevoets, MGJC, Lenroot, RK, Malchow, B, Mandl, RCW, Medel, V, Meinert, S, Morgan, CA, Muehleisen, TW, Nabulsi, L, Opel, N, de la Foz, VO-G, Overs, BJ, Paillere Martinot, M-L, Redlich, R, Marques, TR, Repple, J, Roberts, G, Roshchupkin, GV, Setiaman, N, Shumskaya, E, Stein, F, Sudre, G, Takahashi, S, Thalamuthu, A, Tordesillas-Gutierrez, D, van der Lugt, A, van Haren, NEM, Wardlaw, JM, Wen, W, Westeneng, H-J, Wittfeld, K, Zhu, AH, Zugman, A, Armstrong, NJ, Bonfiglio, G, Bralten, J, Dalvie, S, Davies, G, Di Forti, M, Ding, L, Donohoe, G, Forstner, AJ, Gonzalez-Penas, J, Guimaraes, JPOFT, Homuth, G, Hottenga, J-J, Knol, MJ, Kwok, JBJ, Le Hellard, S, Mather, KA, Milaneschi, Y, Morris, DW, Noethen, MM, Papiol, S, Rietschel, M, Santoro, ML, Steen, VM, Stein, JL, Streit, F, Tankard, RM, Teumer, A, van 't Ent, D, van der Meer, D, van Eijk, KR, Vassos, E, Vazquez-Bourgon, J, Witt, SH, Adams, HHH, Agartz, I, Ames, D, Amunts, K, Andreassen, OA, Arango, C, Banaschewski, T, Baune, BT, Belangero, SI, Bokde, ALW, Boomsma, DI, Bressan, RA, Brodaty, H, Buitelaar, JK, Cahn, W, Caspers, S, Cichon, S, Crespo-Facorro, B, Cox, SR, Dannlowski, U, Elvsashagen, T, Espeseth, T, Falkai, PG, Fisher, SE, Flor, H, Fullerton, JM, Garavan, H, Gowland, PA, Grabe, HJ, Hahn, T, Heinz, A, Hillegers, M, Hoare, J, Hoekstra, PJ, Ikram, MA, Jackowski, AP, Jansen, A, Jonsson, EG, Kahn, RS, Kircher, T, Korgaonkar, MS, Krug, A, Lemaitre, H, Malt, UF, Martinot, J-L, McDonald, C, Mitchell, PB, Muetzel, RL, Murray, RM, Nees, F, Nenadic, I, Oosterlaan, J, Ophoff, RA, Pan, PM, Penninx, BWJH, Poustka, L, Sachdev, PS, Salum, GA, Schofield, PR, Schumann, G, Shaw, P, Sim, K, Smolka, MN, Stein, DJ, Trollor, JN, van den Berg, LH, Veldink, JH, Walter, H, Westlye, LT, Whelan, R, White, T, Wright, MJ, Medland, SE, Franke, B, Thompson, PM, and Hulshoff Pol, HE
Abstract: Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.
Published: 2022

11. Alzheimer's disease research progress in Australia: The Alzheimer's Association International Conference Satellite Symposium in Sydney

Author: Sexton, CE, Anstey, KJ, Baldacci, F, Barnum, CJ, Barron, AM, Blennow, K, Brodaty, H, Burnham, S, Elahi, FM, Gotz, J, Jeon, Y-H, Koronyo-Hamaoui, M, Landau, SM, Lautenschlager, NT, Laws, SM, Lipnicki, DM, Lu, H, Masters, CL, Moyle, W, Nakamura, A, Pasinetti, GM, Rao, N, Rowe, C, Sachdev, PS, Schofield, PR, Sigurdsson, EM, Smith, K, Srikanth, V, Szoeke, C, Tansey, MG, Whitmer, R, Wilcock, D, Wong, TY, Bain, LJ, Carrillo, MC, Sexton, CE, Anstey, KJ, Baldacci, F, Barnum, CJ, Barron, AM, Blennow, K, Brodaty, H, Burnham, S, Elahi, FM, Gotz, J, Jeon, Y-H, Koronyo-Hamaoui, M, Landau, SM, Lautenschlager, NT, Laws, SM, Lipnicki, DM, Lu, H, Masters, CL, Moyle, W, Nakamura, A, Pasinetti, GM, Rao, N, Rowe, C, Sachdev, PS, Schofield, PR, Sigurdsson, EM, Smith, K, Srikanth, V, Szoeke, C, Tansey, MG, Whitmer, R, Wilcock, D, Wong, TY, Bain, LJ, and Carrillo, MC
Abstract: The Alzheimer's Association International Conference held its sixth Satellite Symposium in Sydney, Australia in 2019, highlighting the leadership of Australian researchers in advancing the understanding of and treatment developments for Alzheimer's disease (AD) and other dementias. This leadership includes the Australian Imaging, Biomarker, and Lifestyle Flagship Study of Ageing (AIBL), which has fueled the identification and development of many biomarkers and novel therapeutics. Two multimodal lifestyle intervention studies have been launched in Australia; and Australian researchers have played leadership roles in other global studies in diverse populations. Australian researchers have also played an instrumental role in efforts to understand mechanisms underlying vascular contributions to cognitive impairment and dementia; and through the Women's Healthy Aging Project have elucidated hormonal and other factors that contribute to the increased risk of AD in women. Alleviating the behavioral and psychological symptoms of dementia has also been a strong research and clinical focus in Australia.
Published: 2022

12. Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients (vol 12, 278, 2022)

Author: Schubert, KO, Thalamuthu, A, Amare, AT, Frank, J, Streit, F, Adl, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Marie-Claire, C, Cearns, M, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Clark, SR, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Etain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Heilbronner, U, Herms, S, Hoffmann, P, Hou, L, Hsu, Y-H, Jamain, S, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, J, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, Konig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nothen, MM, Novak, T, O'Donovan, C, Ozaki, N, Osby, U, Papiol, S, Pfennig, A, Pisanu, C, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Tekola-Ayele, F, Tortorella, A, Turecki, G, Veeh, J, Vieta, E, Witt, SH, Roberts, G, Zandi, PP, Alda, M, Bauer, M, McMahon, FJ, Mitchell, PB, Schulze, TG, Rietschel, M, Baune, BT, Schubert, KO, Thalamuthu, A, Amare, AT, Frank, J, Streit, F, Adl, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Marie-Claire, C, Cearns, M, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Clark, SR, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Etain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Heilbronner, U, Herms, S, Hoffmann, P, Hou, L, Hsu, Y-H, Jamain, S, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, J, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, Konig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nothen, MM, Novak, T, O'Donovan, C, Ozaki, N, Osby, U, Papiol, S, Pfennig, A, Pisanu, C, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Tekola-Ayele, F, Tortorella, A, Turecki, G, Veeh, J, Vieta, E, Witt, SH, Roberts, G, Zandi, PP, Alda, M, Bauer, M, McMahon, FJ, Mitchell, PB, Schulze, TG, Rietschel, M, and Baune, BT
Published: 2022

13. Different rates of cognitive decline in autosomal dominant and late-onset Alzheimer disease

Author: Buckles, VD, Xiong, C, Bateman, RJ, Hassenstab, J, Allegri, R, Berman, SB, Chhatwal, JP, Danek, A, Fagan, AM, Ghetti, B, Goate, A, Graff-Radford, N, Jucker, M, Levin, J, Marcus, DS, Masters, CL, McCue, L, McDade, E, Mori, H, Moulder, KL, Noble, JM, Paumier, K, Preische, O, Ringman, JM, Fox, NC, Salloway, S, Schofield, PR, Martins, R, Voglein, J, Morris, JC, Buckles, VD, Xiong, C, Bateman, RJ, Hassenstab, J, Allegri, R, Berman, SB, Chhatwal, JP, Danek, A, Fagan, AM, Ghetti, B, Goate, A, Graff-Radford, N, Jucker, M, Levin, J, Marcus, DS, Masters, CL, McCue, L, McDade, E, Mori, H, Moulder, KL, Noble, JM, Paumier, K, Preische, O, Ringman, JM, Fox, NC, Salloway, S, Schofield, PR, Martins, R, Voglein, J, and Morris, JC
Abstract: As prevention trials advance with autosomal dominant Alzheimer disease (ADAD) participants, understanding the similarities and differences between ADAD and “sporadic” late-onset AD (LOAD) is critical to determine generalizability of findings between these cohorts. Cognitive trajectories of ADAD mutation carriers (MCs) and autopsy-confirmed LOAD individuals were compared to address this question. Longitudinal rates of change on cognitive measures were compared in ADAD MCs (n = 310) and autopsy-confirmed LOAD participants (n = 163) before and after symptom onset (estimated/observed). LOAD participants declined more rapidly in the presymptomatic (preclinical) period and performed more poorly at symptom onset than ADAD participants on a cognitive composite. After symptom onset, however, the younger ADAD MCs declined more rapidly. The similar but not identical cognitive trajectories (declining but at different rates) for ADAD and LOAD suggest common AD pathologies but with some differences.
Published: 2022

14. Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning

Author: Lahti, J, Tuominen, S, Yang, Q, Pergola, G, Ahmad, S, Amin, N, Armstrong, NJ, Beiser, A, Bey, K, Bis, JC, Boerwinkle, E, Bressler, J, Campbell, A, Campbell, H, Chen, Q, Corley, J, Cox, SR, Davies, G, De Jager, PL, Derks, EM, Faul, JD, Fitzpatrick, AL, Fohner, AE, Ford, I, Fornage, M, Gerring, Z, Grabe, HJ, Grodstein, F, Gudnason, V, Simonsick, E, Holliday, EG, Joshi, PK, Kajantie, E, Kaprio, J, Karell, P, Kleineidam, L, Knol, MJ, Kochan, NA, Kwok, JB, Leber, M, Lam, M, Lee, T, Li, S, Loukola, A, Luck, T, Marioni, RE, Mather, KA, Medland, S, Mirza, SS, Nalls, MA, Nho, K, O'Donnell, A, Oldmeadow, C, Painter, J, Pattie, A, Reppermund, S, Risacher, SL, Rose, RJ, Sadashivaiah, V, Scholz, M, Satizabal, CL, Schofield, PW, Schraut, KE, Scott, RJ, Simino, J, Smith, AV, Smith, JA, Stott, DJ, Surakka, I, Teumer, A, Thalamuthu, A, Trompet, S, Turner, ST, van der Lee, SJ, Villringer, A, Voelker, U, Wilson, RS, Wittfeld, K, Vuoksimaa, E, Xia, R, Yaffe, K, Yu, L, Zare, H, Zhao, W, Ames, D, Attia, J, Bennett, DA, Brodaty, H, Chasman, DI, Goldman, AL, Hayward, C, Ikram, MA, Jukema, JW, Kardia, SLR, Lencz, T, Loeffler, M, Mattay, VS, Palotie, A, Psaty, BM, Ramirez, A, Ridker, PM, Riedel-Heller, SG, Sachdev, PS, Saykin, AJ, Scherer, M, Schofield, PR, Sidney, S, Starr, JM, Trollor, J, Ulrich, W, Wagner, M, Weir, DR, Wilson, JF, Wright, MJ, Weinberger, DR, Debette, S, Eriksson, JG, Mosley, TH, Launer, LJ, van Duijn, CM, Deary, IJ, Seshadri, S, Raikkonen, K, Lahti, J, Tuominen, S, Yang, Q, Pergola, G, Ahmad, S, Amin, N, Armstrong, NJ, Beiser, A, Bey, K, Bis, JC, Boerwinkle, E, Bressler, J, Campbell, A, Campbell, H, Chen, Q, Corley, J, Cox, SR, Davies, G, De Jager, PL, Derks, EM, Faul, JD, Fitzpatrick, AL, Fohner, AE, Ford, I, Fornage, M, Gerring, Z, Grabe, HJ, Grodstein, F, Gudnason, V, Simonsick, E, Holliday, EG, Joshi, PK, Kajantie, E, Kaprio, J, Karell, P, Kleineidam, L, Knol, MJ, Kochan, NA, Kwok, JB, Leber, M, Lam, M, Lee, T, Li, S, Loukola, A, Luck, T, Marioni, RE, Mather, KA, Medland, S, Mirza, SS, Nalls, MA, Nho, K, O'Donnell, A, Oldmeadow, C, Painter, J, Pattie, A, Reppermund, S, Risacher, SL, Rose, RJ, Sadashivaiah, V, Scholz, M, Satizabal, CL, Schofield, PW, Schraut, KE, Scott, RJ, Simino, J, Smith, AV, Smith, JA, Stott, DJ, Surakka, I, Teumer, A, Thalamuthu, A, Trompet, S, Turner, ST, van der Lee, SJ, Villringer, A, Voelker, U, Wilson, RS, Wittfeld, K, Vuoksimaa, E, Xia, R, Yaffe, K, Yu, L, Zare, H, Zhao, W, Ames, D, Attia, J, Bennett, DA, Brodaty, H, Chasman, DI, Goldman, AL, Hayward, C, Ikram, MA, Jukema, JW, Kardia, SLR, Lencz, T, Loeffler, M, Mattay, VS, Palotie, A, Psaty, BM, Ramirez, A, Ridker, PM, Riedel-Heller, SG, Sachdev, PS, Saykin, AJ, Scherer, M, Schofield, PR, Sidney, S, Starr, JM, Trollor, J, Ulrich, W, Wagner, M, Weir, DR, Wilson, JF, Wright, MJ, Weinberger, DR, Debette, S, Eriksson, JG, Mosley, TH, Launer, LJ, van Duijn, CM, Deary, IJ, Seshadri, S, and Raikkonen, K
Abstract: Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.
Published: 2022

15. A C6orf10/LOC101929163 locus is associated with age of onset in C9orf72 carriers

Author: Zhang M1, 2 3, Ferrari R4, Tartaglia MC3, 5 6, Keith J7, Surace EI8, Wolf U9, Sato C3, Grinberg M3, Liang Y3, Xi Z3, Dupont K3, McGoldrick P3, Weichert A3, McKeever PM3, Schneider R3, 6 7, McCorkindale MD4, Manzoni C10, Rademakers R11, Graff-Radford NR12, Dickson DW11, Parisi JE13, Boeve BF14, Petersen RC14, Miller BL15, Seeley WW16, van Swieten JC17, van Rooij J17, Pijnenburg Y18, van der Zee J19, Van Broeckhoven C19, Le Ber I21, Van Deerlin V23, Suh E23, Rohrer JD24, Mead S25, Graff C26, Öijerstedt L26, Pickering-Brown S28, Rollinson S28, Rossi G29, Tagliavini F30, Brooks WS31, Dobson-Stone C32, Halliday GM32, Hodges JR32, Piguet O34, Binetti G36, Benussi L37, Ghidoni R37, Nacmias B38, Sorbi S38, Bruni AC40, Galimberti D41, Scarpini E41, Rainero I42, Rubino E42, Clarimon J43, Lleó A43, Ruiz A45, Hernández I45, Pastor P46, Diez-Fairen M46, Borroni B48, Pasquier F49, Deramecourt V49, Lebouvier T49, Perneczky R50, 51 52, Diehl-Schmid J50, Grafman J53, Huey ED55, Mayeux R55, Nalls MA57, Hernandez D57, Singleton A57, Momeni P58, Zeng Z59, Hardy J4, Robertson J3, Zinman L6, 7, Rogaeva E3, 6, International FTD-Genomics Consortium (IFGC), Ferrari R, Hernandez DG, Nalls MA, Rohrer JD, Ramasamy A, Kwok JBJ, Dobson-Stone C, Brooks WS, Schofield PR, Halliday GM, Hodges JR, Piguet O, Bartley L, Thompson E, Hernández I, Ruiz A, Boada M, Borroni B, Padovani A, Cruchaga C, Cairns NJ, Benussi L, Binetti G, Ghidoni R, Forloni G, Albani D, Galimberti D, Fenoglio C, Serpente M, Scarpini E, Clarimón J, Lleó A, Blesa R, Wald Ouml ML, Nilsson K, Nilsson C, Mackenzie IRA, Hsiung GR, Mann DMA, Grafman J, Morris CM, Attems J, Griffiths TD, McKeith IG, Thomas AJ, Pietrini P, Huey ED, Wassermann EM, Baborie A, Jaros E, Tierney MC, Pastor P, Razquin C, Ortega-Cubero S, Alonso E, Perneczky R, Diehl-Schmid J, Alexopoulos P, Kurz A, Rainero I, Rubino E, Pinessi L, Rogaeva E, St George-Hyslop P, Rossi G, Tagliavini F, Giaccone G, Rowe JB, Schlachetzki JCM, Uphill J, Collinge J, Mead S, Danek A, Van Deerlin VM, Grossman M, Trojanowski JQ, van der Zee J, Van Broeckhoven C, Cappa SF, Leber I, Hannequin D, Golfier V, Vercelletto M, Brice A, Nacmias B, Sorbi S, Bagnoli S, Piaceri I, Nielsen JE, Hjermind LE, Riemenschneider M, Mayhaus M, Ibach B, Gasparoni G, Pichler S, Gu W, Rossor MN, Fox NC, Warren JD, Grazia Spillantini M, Morris HR, Rizzu P, Heutink P, Snowden JS, Rollinson S, Richardson A, Gerhard A, Bruni AC, Maletta R, Frangipane F, Cupidi C, Bernardi L, Anfossi M, Gallo M, Elena Conidi M, Smirne N, Rademakers R, Baker M, Dickson DW, Graff-Radford NR, Petersen RC, Knopman D, Josephs KA, Boeve BF, Parisi JE, Seeley WW, Miller BL, Karydas AM, Rosen H, van Swieten JC, Dopper EGP, Seelaar H, Pijnenburg YAL, Scheltens P, Logroscino G, Capozzo R, Novelli V, Puca AA, Franceschi M, Postiglione A, Milan G, Sorrentino P, Kristiansen M, Chiang HH, Graff C, Pasquier F, Rollin A, Deramecourt V, Lebouvier T, Kapogiannis D, Ferrucci L, Pickering-Brown S, Singleton AB, Hardy J, Momeni P, Human genetics, Amsterdam Neuroscience - Neurodegeneration, Neurology, Divisions, Zhang, M1, 2, 3, Ferrari, R4, Tartaglia, Mc3, 5, 6, Keith, J7, Surace, Ei8, Wolf, U9, Sato, C3, Grinberg, M3, Liang, Y3, Xi, Z3, Dupont, K3, Mcgoldrick, P3, Weichert, A3, Mckeever, Pm3, Schneider, R3, 6, 7, Mccorkindale, Md4, Manzoni, C10, Rademakers, R11, Graff-Radford, Nr12, Dickson, Dw11, Parisi, Je13, Boeve, Bf14, Petersen, Rc14, Miller, Bl15, Seeley, Ww16, van Swieten, Jc17, van Rooij, J17, Pijnenburg, Y18, van der Zee, J19, Van Broeckhoven, C19, Le Ber, I21, Van Deerlin, V23, Suh, E23, Rohrer, Jd24, Mead, S25, Graff, C26, Öijerstedt, L26, Pickering-Brown, S28, Rollinson, S28, Rossi, G29, Tagliavini, F30, Brooks, Ws31, Dobson-Stone, C32, Halliday, Gm32, Hodges, Jr32, Piguet, O34, Binetti, G36, Benussi, L37, Ghidoni, R37, Nacmias, B38, Sorbi, S38, Bruni, Ac40, Galimberti, D41, Scarpini, E41, Rainero, I42, Rubino, E42, Clarimon, J43, Lleó, A43, Ruiz, A45, Hernández, I45, Pastor, P46, Diez-Fairen, M46, Borroni, B48, Pasquier, F49, Deramecourt, V49, Lebouvier, T49, Perneczky, R50, 51, 52, Diehl-Schmid, J50, Grafman, J53, Huey, Ed55, Mayeux, R55, Nalls, Ma57, Hernandez, D57, Singleton, A57, Momeni, P58, Zeng, Z59, Hardy, J4, Robertson, J3, Zinman, L6, Rogaeva, E3, International FTD-Genomics Consortium, (IFGC), Ferrari, R, Hernandez, Dg, Nalls, Ma, Rohrer, Jd, Ramasamy, A, Kwok, Jbj, Dobson-Stone, C, Brooks, W, Schofield, Pr, Halliday, Gm, Hodges, Jr, Piguet, O, Bartley, L, Thompson, E, Hernández, I, Ruiz, A, Boada, M, Borroni, B, Padovani, A, Cruchaga, C, Cairns, Nj, Benussi, L, Binetti, G, Ghidoni, R, Forloni, G, Albani, D, Galimberti, D, Fenoglio, C, Serpente, M, Scarpini, E, Clarimón, J, Lleó, A, Blesa, R, Wald Ouml, Ml, Nilsson, K, Nilsson, C, Mackenzie, Ira, Hsiung, Gr, Mann, Dma, Grafman, J, Morris, Cm, Attems, J, Griffiths, Td, Mckeith, Ig, Thomas, Aj, Pietrini, P, Huey, Ed, Wassermann, Em, Baborie, A, Jaros, E, Tierney, Mc, Pastor, P, Razquin, C, Ortega-Cubero, S, Alonso, E, Perneczky, R, Diehl-Schmid, J, Alexopoulos, P, Kurz, A, Rainero, I, Rubino, E, Pinessi, L, Rogaeva, E, St George-Hyslop, P, Rossi, G, Tagliavini, F, Giaccone, G, Rowe, Jb, Schlachetzki, Jcm, Uphill, J, Collinge, J, Mead, S, Danek, A, Van Deerlin, Vm, Grossman, M, Trojanowski, Jq, van der Zee, J, Van Broeckhoven, C, Cappa, Sf, Leber, I, Hannequin, D, Golfier, V, Vercelletto, M, Brice, A, Nacmias, B, Sorbi, S, Bagnoli, S, Piaceri, I, Nielsen, Je, Hjermind, Le, Riemenschneider, M, Mayhaus, M, Ibach, B, Gasparoni, G, Pichler, S, Gu, W, Rossor, Mn, Fox, Nc, Warren, Jd, Grazia Spillantini, M, Morris, Hr, Rizzu, P, Heutink, P, Snowden, J, Rollinson, S, Richardson, A, Gerhard, A, Bruni, Ac, Maletta, R, Frangipane, F, Cupidi, C, Bernardi, L, Anfossi, M, Gallo, M, Elena Conidi, M, Smirne, N, Rademakers, R, Baker, M, Dickson, Dw, Graff-Radford, Nr, Petersen, Rc, Knopman, D, Josephs, Ka, Boeve, Bf, Parisi, Je, Seeley, Ww, Miller, Bl, Karydas, Am, Rosen, H, van Swieten, Jc, Dopper, Egp, Seelaar, H, Pijnenburg, Yal, Scheltens, P, Logroscino, G, Capozzo, R, Novelli, V, Puca, Aa, Franceschi, M, Postiglione, A, Milan, G, Sorrentino, P, Kristiansen, M, Chiang, Hh, Graff, C, Pasquier, F, Rollin, A, Deramecourt, V, Lebouvier, T, Kapogiannis, D, Ferrucci, L, Pickering-Brown, S, Singleton, Ab, Hardy, J, Momeni, P, and Int FTD-Genomics Consortium IFGC
Subjects: Male, Heterozygote, amyotrophic lateral sclerosis, Genotype, genetic association, Age of onset, Polymorphism, Single Nucleotide, frontotemporal dementia, age of onset, C9orf72, Humans, amyotrophic lateral sclerosi, Aged, C9orf72 Protein, Original Articles, DNA Methylation, Middle Aged, Amyotrophic lateral sclerosis, Gene Expression Regulation, Genetic association, CpG Islands, Female, Human medicine, Neurology (clinical), Frontotemporal dementia
Abstract: Discovery of disease age-of-onset modifiers is important for clinical trials and drug design. Zhang et al. perform a genome-wide analysis of epigenetic functional polymorphisms and identify an association between the C6orf10/LOC101929163 locus and age of FTD/ALS onset. The risk allele may be associated with a pro-inflammatory state in the brain., The G4C2-repeat expansion in C9orf72 is the most common known cause of amyotrophic lateral sclerosis and frontotemporal dementia. The high phenotypic heterogeneity of C9orf72 patients includes a wide range in age of onset, modifiers of which are largely unknown. Age of onset could be influenced by environmental and genetic factors both of which may trigger DNA methylation changes at CpG sites. We tested the hypothesis that age of onset in C9orf72 patients is associated with some common single nucleotide polymorphisms causing a gain or loss of CpG sites and thus resulting in DNA methylation alterations. Combined analyses of epigenetic and genetic data have the advantage of detecting functional variants with reduced likelihood of false negative results due to excessive correction for multiple testing in genome-wide association studies. First, we estimated the association between age of onset in C9orf72 patients (n = 46) and the DNA methylation levels at all 7603 CpG sites available on the 450 k BeadChip that are mapped to common single nucleotide polymorphisms. This was followed by a genetic association study of the discovery (n = 144) and replication (n = 187) C9orf72 cohorts. We found that age of onset was reproducibly associated with polymorphisms within a 124.7 kb linkage disequilibrium block tagged by top-significant variation, rs9357140, and containing two overlapping genes (LOC101929163 and C6orf10). A meta-analysis of all 331 C9orf72 carriers revealed that every A-allele of rs9357140 reduced hazard by 30% (P = 0.0002); and the median age of onset in AA-carriers was 6 years later than GG-carriers. In addition, we investigated a cohort of C9orf72 negative patients (n = 2634) affected by frontotemporal dementia and/or amyotrophic lateral sclerosis; and also found that the AA-genotype of rs9357140 was associated with a later age of onset (adjusted P = 0.007 for recessive model). Phenotype analyses detected significant association only in the largest subgroup of patients with frontotemporal dementia (n = 2142, adjusted P = 0.01 for recessive model). Gene expression studies of frontal cortex tissues from 25 autopsy cases affected by amyotrophic lateral sclerosis revealed that the G-allele of rs9357140 is associated with increased brain expression of LOC101929163 (a non-coding RNA) and HLA-DRB1 (involved in initiating immune responses), while the A-allele is associated with their reduced expression. Our findings suggest that carriers of the rs9357140 GG-genotype (linked to an earlier age of onset) might be more prone to be in a pro-inflammatory state (e.g. by microglia) than AA-carriers. Further, investigating the functional links within the C6orf10/LOC101929163/HLA-DRB1 pathway will be critical to better define age-dependent pathogenesis of frontotemporal dementia and amyotrophic lateral sclerosis.
Published: 2018

16. The BDNFVal66Met SNP modulates the association between beta-amyloid and hippocampal disconnection in Alzheimer’s disease

Author: Franzmeier, N, Ren, J, Damm, A, Monté-Rubio, G, Boada, M, Ruiz, A, Ramirez, A, Jessen, F, Düzel, E, Rodríguez Gómez, O, Benzinger, T, Goate, A, Karch, CM, Fagan, AM, McDade, E, Buerger, K, Levin, J, Duering, M, Dichgans, M, Suárez-Calvet, M, Haass, C, Gordon, BA, Lim, YY, Masters, CL, Janowitz, D, Catak, C, Wolfsgruber, S, Wagner, M, Milz, E, Moreno-Grau, S, Teipel, S, Grothe, MJ, Kilimann, I, Rossor, M, Fox, N, Laske, C, Chhatwal, J, Falkai, P, Perneczky, R, Lee, JH, Spottke, A, Boecker, H, Brosseron, F, Fliessbach, K, Heneka, MT, Nestor, P, Peters, O, Fuentes, M, Menne, F, Priller, J, Spruth, EJ, Franke, C, Schneider, A, Westerteicher, C, Speck, O, Wiltfang, J, Bartels, C, Araque Caballero, MÁ, Metzger, C, Bittner, D, Salloway, S, Danek, A, Hassenstab, J, Yakushev, I, Schofield, PR, Morris, JC, Bateman, RJ, Ewers, M, Franzmeier, N, Ren, J, Damm, A, Monté-Rubio, G, Boada, M, Ruiz, A, Ramirez, A, Jessen, F, Düzel, E, Rodríguez Gómez, O, Benzinger, T, Goate, A, Karch, CM, Fagan, AM, McDade, E, Buerger, K, Levin, J, Duering, M, Dichgans, M, Suárez-Calvet, M, Haass, C, Gordon, BA, Lim, YY, Masters, CL, Janowitz, D, Catak, C, Wolfsgruber, S, Wagner, M, Milz, E, Moreno-Grau, S, Teipel, S, Grothe, MJ, Kilimann, I, Rossor, M, Fox, N, Laske, C, Chhatwal, J, Falkai, P, Perneczky, R, Lee, JH, Spottke, A, Boecker, H, Brosseron, F, Fliessbach, K, Heneka, MT, Nestor, P, Peters, O, Fuentes, M, Menne, F, Priller, J, Spruth, EJ, Franke, C, Schneider, A, Westerteicher, C, Speck, O, Wiltfang, J, Bartels, C, Araque Caballero, MÁ, Metzger, C, Bittner, D, Salloway, S, Danek, A, Hassenstab, J, Yakushev, I, Schofield, PR, Morris, JC, Bateman, RJ, and Ewers, M
Abstract: In Alzheimer’s disease (AD), a single-nucleotide polymorphism in the gene encoding brain-derived neurotrophic factor (BDNFVal66Met) is associated with worse impact of primary AD pathology (beta-amyloid, Aβ) on neurodegeneration and cognitive decline, rendering BDNFVal66Met an important modulating factor of cognitive impairment in AD. However, the effect of BDNFVal66Met on functional networks that may underlie cognitive impairment in AD is poorly understood. Using a cross-validation approach, we first explored in subjects with autosomal dominant AD (ADAD) from the Dominantly Inherited Alzheimer Network (DIAN) the effect of BDNFVal66Met on resting-state fMRI assessed functional networks. In seed-based connectivity analysis of six major large-scale networks, we found a stronger decrease of hippocampus (seed) to medial-frontal connectivity in the BDNFVal66Met carriers compared to BDNFVal homozogytes. BDNFVal66Met was not associated with connectivity in any other networks. Next, we tested whether the finding of more pronounced decrease in hippocampal-medial-frontal connectivity in BDNFVal66Met could be also found in elderly subjects with sporadically occurring Aβ, including a group with subjective cognitive decline (N = 149, FACEHBI study) and a group ranging from preclinical to AD dementia (N = 114, DELCODE study). In both of these independently recruited groups, BDNFVal66Met was associated with a stronger effect of more abnormal Aβ-levels (assessed by biofluid-assay or amyloid-PET) on hippocampal-medial-frontal connectivity decreases, controlled for hippocampus volume and other confounds. Lower hippocampal-medial-frontal connectivity was associated with lower global cognitive performance in the DIAN and DELCODE studies. Together these results suggest that BDNFVal66Met is selectively associated with a higher vulnerability of hippocampus-frontal connectivity to primary AD pathology, resulting in greater AD-related cognitive impairment.
Published: 2021

17. HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders

Author: Le Clerc, S, Lombardi, L, Baune, BT, Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Cearns, M, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, YH, Shekhtman, T, Adli, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, HC, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Étain, B, Jamain, S, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Jiménez, E, Kahn, JP, Kassem, L, Kuo, PH, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, König, B, Kusumi, I, Laje, G, Landén, M, Lavebratt, C, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, Colom, F, Millischer, V, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Novák, T, O’Donovan, C, Ozaki, N, Ösby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Pisanu, C, Squassina, A, Le Clerc, S, Lombardi, L, Baune, BT, Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Cearns, M, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, YH, Shekhtman, T, Adli, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, HC, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Étain, B, Jamain, S, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Jiménez, E, Kahn, JP, Kassem, L, Kuo, PH, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, König, B, Kusumi, I, Laje, G, Landén, M, Lavebratt, C, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, Colom, F, Millischer, V, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Novák, T, O’Donovan, C, Ozaki, N, Ösby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Pisanu, C, and Squassina, A
Abstract: Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 × 10−3; FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.
Published: 2021

18. Alzheimer's disease research progress in Australia: The Alzheimer's Association International Conference Satellite Symposium in Sydney

Author: Sexton, CE, Anstey, KJ, Baldacci, F, Barnum, CJ, Barron, AM, Blennow, K, Brodaty, H, Burnham, S, Elahi, FM, Götz, J, Jeon, YH, Koronyo-Hamaoui, M, Landau, SM, Lautenschlager, NT, Laws, SM, Lipnicki, DM, Lu, H, Masters, CL, Moyle, W, Nakamura, A, Pasinetti, GM, Rao, N, Rowe, C, Sachdev, PS, Schofield, PR, Sigurdsson, EM, Smith, K, Srikanth, V, Szoeke, C, Tansey, MG, Whitmer, R, Wilcock, D, Wong, TY, Bain, LJ, Carrillo, MC, Sexton, CE, Anstey, KJ, Baldacci, F, Barnum, CJ, Barron, AM, Blennow, K, Brodaty, H, Burnham, S, Elahi, FM, Götz, J, Jeon, YH, Koronyo-Hamaoui, M, Landau, SM, Lautenschlager, NT, Laws, SM, Lipnicki, DM, Lu, H, Masters, CL, Moyle, W, Nakamura, A, Pasinetti, GM, Rao, N, Rowe, C, Sachdev, PS, Schofield, PR, Sigurdsson, EM, Smith, K, Srikanth, V, Szoeke, C, Tansey, MG, Whitmer, R, Wilcock, D, Wong, TY, Bain, LJ, and Carrillo, MC
Abstract: The Alzheimer's Association International Conference held its sixth Satellite Symposium in Sydney, Australia in 2019, highlighting the leadership of Australian researchers in advancing the understanding of and treatment developments for Alzheimer's disease (AD) and other dementias. This leadership includes the Australian Imaging, Biomarker, and Lifestyle Flagship Study of Ageing (AIBL), which has fueled the identification and development of many biomarkers and novel therapeutics. Two multimodal lifestyle intervention studies have been launched in Australia; and Australian researchers have played leadership roles in other global studies in diverse populations. Australian researchers have also played an instrumental role in efforts to understand mechanisms underlying vascular contributions to cognitive impairment and dementia; and through the Women's Healthy Aging Project have elucidated hormonal and other factors that contribute to the increased risk of AD in women. Alleviating the behavioral and psychological symptoms of dementia has also been a strong research and clinical focus in Australia.
Published: 2021

19. Investigating olfactory gene variation and odour identification in older adults

Author: Raj, S, Thalamuthu, A, Armstrong, NJ, Wright, MJ, Kwok, JB, Trollor, JN, Ames, D, Schofield, PR, Brodaty, H, Sachdev, PS, Mather, KA, Raj, S, Thalamuthu, A, Armstrong, NJ, Wright, MJ, Kwok, JB, Trollor, JN, Ames, D, Schofield, PR, Brodaty, H, Sachdev, PS, and Mather, KA
Abstract: Ageing is associated with a decrease in odour identification. Additionally, deficits in olfaction have been linked to age-related disease and mortality. Heritability studies suggest genetic variation contributes to olfactory identification. The olfactory receptor (OR) gene family is the largest in the human genome and responsible for overall odour identification. In this study, we sought to find olfactory gene family variants associated with individual and overall odour identification and to examine the relationships between polygenic risk scores (PRS) for olfactory-related phenotypes and olfaction. Participants were Caucasian older adults from the Sydney Memory and Ageing Study and the Older Australian Twins Study with genome-wide genotyping data (n = 1395, mean age = 75.52 ± 6.45). The Brief-Smell Identification Test (BSIT) was administered in both cohorts. PRS were calculated from independent GWAS summary statistics for Alzheimer’s disease (AD), white matter hyperintensities (WMH), Parkinson’s disease (PD), hippocampal volume and smoking. Associations with olfactory receptor genes (n = 967), previously identified candidate olfaction-related SNPs (n = 36) and different PRS with BSIT scores (total and individual smells) were examined. All of the relationships were analysed using generalised linear mixed models (GLMM), adjusted for age and sex. Genes with suggestive evidence for odour identification were found for 8 of the 12 BSIT items. Thirteen out of 36 candidate SNPs previously identified from the literature were suggestively associated with several individual BSIT items but not total score. PRS for smoking, WMH and PD were negatively associated with chocolate identification. This is the first study to conduct genetic analyses with individual odorant identification, which found suggestive olfactory-related genes and genetic variants for multiple individual BSIT odours. Replication in independent and larger cohorts is needed.
Published: 2021

20. A linkage and exome study of multiplex families with bipolar disorder implicates rare coding variants of ANK3 and additional rare alleles at 10q11-q21

Author: Toma, C, Shaw, AD, Heath, A, Pierce, KD, Mitchell, PB, Schofield, PR, Fullerton, JM, Toma, C, Shaw, AD, Heath, A, Pierce, KD, Mitchell, PB, Schofield, PR, and Fullerton, JM
Abstract: Background: Bipolar disorder is a highly heritable psychiatric condition for which specific genetic factors remain largely unknown. In the present study, we used combined whole-exome sequencing and linkage analysis to identify risk loci and dissect the contribution of common and rare variants in families with a high density of illness. Methods: Overall, 117 participants from 15 Australian extended families with bipolar disorder (72 with affective disorder, including 50 with bipolar disorder type I or II, 13 with schizoaffective disorder–manic type and 9 with recurrent unipolar disorder) underwent whole-exome sequencing. We performed genome-wide linkage analysis using MERLIN and conditional linkage analysis using LAMP. We assessed the contribution of potentially functional rare variants using a genebased segregation test. Results: We identified a significant linkage peak on chromosome 10q11-q21 (maximal single nucleotide polymorphism = rs10761725; exponential logarithm of the odds [LODexp] = 3.03; empirical p = 0.046). The linkage interval spanned 36 protein-coding genes, including a gene associated with bipolar disorder, ankyrin 3 (ANK3). Conditional linkage analysis showed that common ANK3 risk variants previously identified in genome-wide association studies — or variants in linkage disequilibrium with those variants — did not explain the linkage signal (rs10994397 LOD = 0.63; rs9804190 LOD = 0.04). A family-based segregation test with 34 rare variants from 14 genes under the linkage interval suggested rare variant contributions of 3 brain-expressed genes: NRBF2 (p = 0.005), PCDH15 (p = 0.002) and ANK3 (p = 0.014). Limitations: We did not examine non-coding variants, but they may explain the remaining linkage signal. Conclusion: Combining family-based linkage analysis with next-generation sequencing data is effective for identifying putative disease genes and specific risk variants in complex disorders. We identified rare missense variants in ANK3, PCDH15 and NRBF
Published: 2021

21. Prediction of lithium response using genomic data

Author: Stone, W, Nunes, A, Akiyama, K, Akula, N, Ardau, R, Aubry, JM, Backlund, L, Bauer, M, Bellivier, F, Cervantes, P, Chen, HC, Chillotti, C, Cruceanu, C, Dayer, A, Degenhardt, F, Del Zompo, M, Forstner, AJ, Frye, M, Fullerton, JM, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hou, L, Jiménez, E, Kato, T, Kelsoe, J, Kittel-Schneider, S, Kuo, PH, Kusumi, I, Lavebratt, C, Manchia, M, Martinsson, L, Mattheisen, M, McMahon, FJ, Millischer, V, Mitchell, PB, Nöthen, MM, O’Donovan, C, Ozaki, N, Pisanu, C, Reif, A, Rietschel, M, Rouleau, G, Rybakowski, J, Schalling, M, Schofield, PR, Schulze, TG, Severino, G, Squassina, A, Veeh, J, Vieta, E, Trappenberg, T, Alda, M, Stone, W, Nunes, A, Akiyama, K, Akula, N, Ardau, R, Aubry, JM, Backlund, L, Bauer, M, Bellivier, F, Cervantes, P, Chen, HC, Chillotti, C, Cruceanu, C, Dayer, A, Degenhardt, F, Del Zompo, M, Forstner, AJ, Frye, M, Fullerton, JM, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hou, L, Jiménez, E, Kato, T, Kelsoe, J, Kittel-Schneider, S, Kuo, PH, Kusumi, I, Lavebratt, C, Manchia, M, Martinsson, L, Mattheisen, M, McMahon, FJ, Millischer, V, Mitchell, PB, Nöthen, MM, O’Donovan, C, Ozaki, N, Pisanu, C, Reif, A, Rietschel, M, Rouleau, G, Rybakowski, J, Schalling, M, Schofield, PR, Schulze, TG, Severino, G, Squassina, A, Veeh, J, Vieta, E, Trappenberg, T, and Alda, M
Abstract: Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with a machine learning (ML) approach using genomic data. Using the largest existing genomic dataset in the lithium response literature (n = 2210 across 14 international sites; 29% responders), we evaluated the degree to which lithium response could be predicted based on 47,465 genotyped single nucleotide polymorphisms using a supervised ML approach. Under appropriate cross-validation procedures, lithium response could be predicted to above-chance levels in two constituent sites (Halifax, Cohen’s kappa 0.15, 95% confidence interval, CI [0.07, 0.24]; and Würzburg, kappa 0.2 [0.1, 0.3]). Variants with shared importance in these models showed over-representation of postsynaptic membrane related genes. Lithium response was not predictable in the pooled dataset (kappa 0.02 [− 0.01, 0.04]), although non-trivial performance was achieved within a restricted dataset including only those patients followed prospectively (kappa 0.09 [0.04, 0.14]). Genomic classification of lithium response remains a promising but difficult task. Classification performance could potentially be improved by further harmonization of data collection procedures.
Published: 2021

22. Cortical mediation of relationships between dopamine receptor D2 and cognition is absent in youth at risk of bipolar disorder

Author: Overs, BJ, Lenroot, RK, Roberts, G, Green, MJ, Toma, C, Hadzi-Pavlovic, D, Pierce, KD, Schofield, PR, Mitchell, PB, Fullerton, JM, Overs, BJ, Lenroot, RK, Roberts, G, Green, MJ, Toma, C, Hadzi-Pavlovic, D, Pierce, KD, Schofield, PR, Mitchell, PB, and Fullerton, JM
Abstract: Bipolar disorder is associated with cognitive deficits and cortical changes for which the developmental dynamics are not well understood. The dopamine D2 receptor (DRD2) gene has been associated with both psychiatric disorders and cognitive variability. Here we examined the mediating role of brain structure in the relationship between DRD2 genomic variation and cognitive performance, with target cortical regions selected based on evidence of association with DRD2, bipolar disorder and/or cognition from prior literature. Participants (n = 143) were aged 12–30 years and comprised 62 first-degree relatives of bipolar patients (deemed ‘at-risk’), 55 controls, and 26 patients with established bipolar disorder; all were unrelated Caucasian individuals with complete data across the three required modalities (structural magnetic resonance imaging, neuropsychological and genetic data). A DRD2 haplotype was derived from three functional polymorphisms (rs1800497, rs1076560, rs2283265) associated with alternative splicing (i.e., D2-short/-long isoforms). Moderated mediation analyses explored group differences in relationships between this DRD2 haplotype, three structural brain networks which subsume the identified cortical regions of interest (frontoparietal, dorsal-attention, and ventral-attention), and three cognitive indices (intelligence, attention, and immediate memory). Controls who were homozygous for the DRD2 major haplotype demonstrated greater cognitive performance as a result of dorsal-attention network mediation. However, this association was absent in the ‘at-risk’ group. This study provides the first evidence of a functional DRD2-brain-cognition pathway. The absence of typical brain-cognition relationships in young ‘at-risk’ individuals may reflect biological differences that precede illness onset. Further insight into early pathogenic processes may facilitate targeted early interventions.
Published: 2021

23. 1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans

Author: Sonderby, IE, van der Meer, D, Moreau, C, Kaufmann, T, Walters, GB, Ellegaard, M, Abdellaoui, A, Ames, D, Amunts, K, Andersson, M, Armstrong, NJ, Bernard, M, Blackburn, NB, Blangero, J, Boomsma, DI, Brodaty, H, Brouwer, RM, Buelow, R, Boen, R, Cahn, W, Calhoun, VD, Caspers, S, Ching, CRK, Cichon, S, Ciufolini, S, Crespo-Facorro, B, Curran, JE, Dale, AM, Dalvie, S, Dazzan, P, de Geus, EJC, de Zubicaray, GI, de Zwarte, SMC, Desrivieres, S, Doherty, JL, Donohoe, G, Draganski, B, Ehrlich, S, Eising, E, Espeseth, T, Fejgin, K, Fisher, SE, Fladby, T, Frei, O, Frouin, V, Fukunaga, M, Gareau, T, Ge, T, Glahn, DC, Grabe, HJ, Groenewold, NA, Gustafsson, O, Haavik, J, Haberg, AK, Hall, J, Hashimoto, R, Hehir-Kwa, JY, Hibar, DP, Hillegers, MHJ, Hoffmann, P, Holleran, L, Holmes, AJ, Homuth, G, Hottenga, J-J, Hulshoff Pol, HE, Ikeda, M, Jahanshad, N, Jockwitz, C, Johansson, S, Joensson, EG, Jorgensen, NR, Kikuchi, M, Knowles, EEM, Kumar, K, Le Hellard, S, Leu, C, Linden, DEJ, Liu, J, Lundervold, A, Lundervold, AJ, Maillard, AM, Martin, NG, Martin-Brevet, S, Mather, KA, Mathias, SR, McMahon, KL, McRae, AF, Medland, SE, Meyer-Lindenberg, A, Moberget, T, Modenato, C, Sanchez, JM, Morris, DW, Muehleisen, TW, Murray, RM, Nielsen, J, Nordvik, JE, Nyberg, L, Loohuis, LMO, Ophoff, RA, Owen, MJ, Paus, T, Pausova, Z, Peralta, JM, Pike, GB, Prieto, C, Quinlan, EB, Reinbold, CS, Marques, TR, Rucker, JJH, Sachdev, PS, Sando, SB, Schofield, PR, Schork, AJ, Schumann, G, Shin, J, Shumskaya, E, Silva, AI, Sisodiya, SM, Steen, VM, Stein, DJ, Strike, LT, Suzuki, IK, Tamnes, CK, Teumer, A, Thalamuthu, A, Tordesillas-Gutierrez, D, Uhlmann, A, Ulfarsson, MO, van 't Ent, D, van den Bree, MBM, Vanderhaeghen, P, Vassos, E, Wen, W, Wittfeld, K, Wright, MJ, Agartz, I, Djurovic, S, Westlye, LT, Stefansson, H, Stefansson, K, Jacquemont, S, Thompson, PM, Andreassen, OA, Sonderby, IE, van der Meer, D, Moreau, C, Kaufmann, T, Walters, GB, Ellegaard, M, Abdellaoui, A, Ames, D, Amunts, K, Andersson, M, Armstrong, NJ, Bernard, M, Blackburn, NB, Blangero, J, Boomsma, DI, Brodaty, H, Brouwer, RM, Buelow, R, Boen, R, Cahn, W, Calhoun, VD, Caspers, S, Ching, CRK, Cichon, S, Ciufolini, S, Crespo-Facorro, B, Curran, JE, Dale, AM, Dalvie, S, Dazzan, P, de Geus, EJC, de Zubicaray, GI, de Zwarte, SMC, Desrivieres, S, Doherty, JL, Donohoe, G, Draganski, B, Ehrlich, S, Eising, E, Espeseth, T, Fejgin, K, Fisher, SE, Fladby, T, Frei, O, Frouin, V, Fukunaga, M, Gareau, T, Ge, T, Glahn, DC, Grabe, HJ, Groenewold, NA, Gustafsson, O, Haavik, J, Haberg, AK, Hall, J, Hashimoto, R, Hehir-Kwa, JY, Hibar, DP, Hillegers, MHJ, Hoffmann, P, Holleran, L, Holmes, AJ, Homuth, G, Hottenga, J-J, Hulshoff Pol, HE, Ikeda, M, Jahanshad, N, Jockwitz, C, Johansson, S, Joensson, EG, Jorgensen, NR, Kikuchi, M, Knowles, EEM, Kumar, K, Le Hellard, S, Leu, C, Linden, DEJ, Liu, J, Lundervold, A, Lundervold, AJ, Maillard, AM, Martin, NG, Martin-Brevet, S, Mather, KA, Mathias, SR, McMahon, KL, McRae, AF, Medland, SE, Meyer-Lindenberg, A, Moberget, T, Modenato, C, Sanchez, JM, Morris, DW, Muehleisen, TW, Murray, RM, Nielsen, J, Nordvik, JE, Nyberg, L, Loohuis, LMO, Ophoff, RA, Owen, MJ, Paus, T, Pausova, Z, Peralta, JM, Pike, GB, Prieto, C, Quinlan, EB, Reinbold, CS, Marques, TR, Rucker, JJH, Sachdev, PS, Sando, SB, Schofield, PR, Schork, AJ, Schumann, G, Shin, J, Shumskaya, E, Silva, AI, Sisodiya, SM, Steen, VM, Stein, DJ, Strike, LT, Suzuki, IK, Tamnes, CK, Teumer, A, Thalamuthu, A, Tordesillas-Gutierrez, D, Uhlmann, A, Ulfarsson, MO, van 't Ent, D, van den Bree, MBM, Vanderhaeghen, P, Vassos, E, Wen, W, Wittfeld, K, Wright, MJ, Agartz, I, Djurovic, S, Westlye, LT, Stefansson, H, Stefansson, K, Jacquemont, S, Thompson, PM, and Andreassen, OA
Abstract: Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.
Published: 2021

24. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Author: Mullins, N, Forstner, AJ, O'Connell, KS, Coombes, B, Coleman, JR, Qiao, Z, Als, TD, Bigdeli, TB, Borte, S, Bryois, J, Charney, AW, Drange, OK, Gandal, MJ, Hagenaars, SP, Ikeda, M, Kamitaki, N, Kim, M, Krebs, K, Panagiotaropoulou, G, Schilder, BM, Sloofman, LG, Steinberg, S, Trubetskoy, V, Winsvold, BS, Won, H-H, Abramova, L, Adorjan, K, Agerbo, E, Al Eissa, M, Albani, D, Alliey-Rodriguez, N, Anjorin, A, Antilla, V, Antoniou, A, Awasthi, S, Baek, JH, Baekvad-Hansen, M, Bass, N, Bauer, M, Beins, EC, Bergen, SE, Birner, A, Pedersen, CB, Boen, E, Boks, MP, Bosch, R, Brum, M, Brumpton, BM, Brunkhorst-Kanaan, N, Budde, M, Bybjerg-Grauholm, J, Byerley, W, Cairns, M, Casas, M, Cervantes, P, Clarke, T-K, Cruceanu, C, Cuellar-Barboza, A, Cunningham, J, Curtis, D, Czerski, PM, Dale, AM, Dalkner, N, David, FS, Degenhardt, F, Djurovic, S, Dobbyn, AL, Douzenis, A, Elvsashagen, T, Escott-Price, V, Ferrier, IN, Fiorentino, A, Foroud, TM, Forty, L, Frank, J, Frei, O, Freimer, NB, Frisen, L, Gade, K, Garnham, J, Gelernter, J, Pedersen, MG, Gizer, IR, Gordon, SD, Gordon-Smith, K, Greenwood, TA, Grove, J, Guzman-Parra, J, Ha, K, Haraldsson, M, Hautzinger, M, Heilbronner, U, Hellgren, D, Herms, S, Hoffmann, P, Holmans, PA, Huckins, L, Jamain, S, Johnson, JS, Kalman, JL, Kamatani, Y, Kennedy, JL, Kittel-Schneider, S, Knowles, JA, Kogevinas, M, Koromina, M, Kranz, TM, Kranzler, HR, Kubo, M, Kupka, R, Kushner, SA, Lavebratt, C, Lawrence, J, Leber, M, Lee, H-J, Lee, PH, Levy, SE, Lewis, C, Liao, C, Lucae, S, Lundberg, M, MacIntyre, DJ, Maier, W, Maihofer, A, Malaspina, D, Maratou, E, Martinsson, L, Mattheisen, M, McCarroll, SA, McGregor, NW, McGuffin, P, McKay, JD, Medeiros, H, Medland, SE, Millischer, V, Montgomery, GW, Moran, JL, Morris, DW, Muhleisen, TW, O'Brien, N, O'Donovan, C, Loohuis, LMO, Oruc, L, Papiol, S, Pardinas, AF, Perry, A, Pfennig, A, Porichi, E, Potash, JB, Quested, D, Raj, T, Rapaport, MH, DePaulo, JR, Regeer, EJ, Rice, JP, Rivas, F, Rivera, M, Roth, J, Roussos, P, Ruderfer, DM, Sanchez-Mora, C, Schulte, EC, Senner, F, Sharp, S, Shilling, PD, Sigurdsson, E, Sirignano, L, Slaney, C, Smeland, OB, Sobell, JL, Hansen, CS, Artigas, MS, Spijker, AT, Stein, DJ, Strauss, JS, Swiatkowska, B, Terao, C, Thorgeirsson, TE, Toma, C, Tooney, P, Tsermpini, E-E, Vawter, MP, Vedder, H, Walters, JTR, Witt, SH, Xi, S, Xu, W, Yang, JMK, Young, AH, Young, H, Zandi, PP, Zhou, H, Zillich, L, Adolfsson, R, Agartz, I, Alda, M, Alfredsson, L, Babadjanova, G, Backlund, L, Baune, BT, Bellivier, F, Bengesser, S, Berrettini, WH, Blackwood, DHR, Boehnke, M, Borglum, AD, Breen, G, Carr, VJ, Catts, S, Corvin, A, Craddock, N, Dannlowski, U, Dikeos, D, Esko, T, Etain, B, Ferentinos, P, Frye, M, Fullerton, JM, Gawlik, M, Gershon, ES, Goes, F, Green, MJ, Grigoroiu-Serbanescu, M, Hauser, J, Henskens, F, Hillert, J, Hong, KS, Hougaard, DM, Hultman, CM, Hveem, K, Iwata, N, Jablensky, A, Jones, I, Jones, LA, Kahn, RS, Kelsoe, JR, Kirov, G, Landen, M, Leboyer, M, Lewis, CM, Li, QS, Lissowska, J, Lochner, C, Loughland, C, Martin, NG, Mathews, CA, Mayoral, F, McElroy, SL, McIntosh, AM, McMahon, FJ, Melle, I, Michie, P, Milani, L, Mitchell, PB, Morken, G, Mors, O, Mortensen, PB, Mowry, B, Muller-Myhsok, B, Myers, RM, Neale, BM, Nievergelt, CM, Nordentoft, M, Nothen, MM, ODonovan, MC, Oedegaard, KJ, Olsson, T, Owen, MJ, Paciga, SA, Pantelis, C, Pato, C, Pato, MT, Patrinos, GP, Perlis, RH, Posthuma, D, Ramos-Quiroga, JA, Reif, A, Reininghaus, EZ, Ribases, M, Rietschel, M, Ripke, S, Rouleau, GA, Saito, T, Schall, U, Schalling, M, Schofield, PR, Schulze, TG, Scott, LJ, Scott, RJ, Serretti, A, Weickert, CS, Smoller, JW, Stefansson, H, Stefansson, K, Stordal, E, Streit, F, Sullivan, PF, Turecki, G, Vaaler, AE, Vieta, E, Vincent, JB, Waldman, ID, Weickert, TW, Werge, T, Wray, NR, Zwart, J, Biernacka, JM, Nurnberger, J, Cichon, S, Edenberg, HJ, Stahl, EA, McQuillin, A, Di Florio, A, Ophoff, RA, Andreassen, OA, Mullins, N, Forstner, AJ, O'Connell, KS, Coombes, B, Coleman, JR, Qiao, Z, Als, TD, Bigdeli, TB, Borte, S, Bryois, J, Charney, AW, Drange, OK, Gandal, MJ, Hagenaars, SP, Ikeda, M, Kamitaki, N, Kim, M, Krebs, K, Panagiotaropoulou, G, Schilder, BM, Sloofman, LG, Steinberg, S, Trubetskoy, V, Winsvold, BS, Won, H-H, Abramova, L, Adorjan, K, Agerbo, E, Al Eissa, M, Albani, D, Alliey-Rodriguez, N, Anjorin, A, Antilla, V, Antoniou, A, Awasthi, S, Baek, JH, Baekvad-Hansen, M, Bass, N, Bauer, M, Beins, EC, Bergen, SE, Birner, A, Pedersen, CB, Boen, E, Boks, MP, Bosch, R, Brum, M, Brumpton, BM, Brunkhorst-Kanaan, N, Budde, M, Bybjerg-Grauholm, J, Byerley, W, Cairns, M, Casas, M, Cervantes, P, Clarke, T-K, Cruceanu, C, Cuellar-Barboza, A, Cunningham, J, Curtis, D, Czerski, PM, Dale, AM, Dalkner, N, David, FS, Degenhardt, F, Djurovic, S, Dobbyn, AL, Douzenis, A, Elvsashagen, T, Escott-Price, V, Ferrier, IN, Fiorentino, A, Foroud, TM, Forty, L, Frank, J, Frei, O, Freimer, NB, Frisen, L, Gade, K, Garnham, J, Gelernter, J, Pedersen, MG, Gizer, IR, Gordon, SD, Gordon-Smith, K, Greenwood, TA, Grove, J, Guzman-Parra, J, Ha, K, Haraldsson, M, Hautzinger, M, Heilbronner, U, Hellgren, D, Herms, S, Hoffmann, P, Holmans, PA, Huckins, L, Jamain, S, Johnson, JS, Kalman, JL, Kamatani, Y, Kennedy, JL, Kittel-Schneider, S, Knowles, JA, Kogevinas, M, Koromina, M, Kranz, TM, Kranzler, HR, Kubo, M, Kupka, R, Kushner, SA, Lavebratt, C, Lawrence, J, Leber, M, Lee, H-J, Lee, PH, Levy, SE, Lewis, C, Liao, C, Lucae, S, Lundberg, M, MacIntyre, DJ, Maier, W, Maihofer, A, Malaspina, D, Maratou, E, Martinsson, L, Mattheisen, M, McCarroll, SA, McGregor, NW, McGuffin, P, McKay, JD, Medeiros, H, Medland, SE, Millischer, V, Montgomery, GW, Moran, JL, Morris, DW, Muhleisen, TW, O'Brien, N, O'Donovan, C, Loohuis, LMO, Oruc, L, Papiol, S, Pardinas, AF, Perry, A, Pfennig, A, Porichi, E, Potash, JB, Quested, D, Raj, T, Rapaport, MH, DePaulo, JR, Regeer, EJ, Rice, JP, Rivas, F, Rivera, M, Roth, J, Roussos, P, Ruderfer, DM, Sanchez-Mora, C, Schulte, EC, Senner, F, Sharp, S, Shilling, PD, Sigurdsson, E, Sirignano, L, Slaney, C, Smeland, OB, Sobell, JL, Hansen, CS, Artigas, MS, Spijker, AT, Stein, DJ, Strauss, JS, Swiatkowska, B, Terao, C, Thorgeirsson, TE, Toma, C, Tooney, P, Tsermpini, E-E, Vawter, MP, Vedder, H, Walters, JTR, Witt, SH, Xi, S, Xu, W, Yang, JMK, Young, AH, Young, H, Zandi, PP, Zhou, H, Zillich, L, Adolfsson, R, Agartz, I, Alda, M, Alfredsson, L, Babadjanova, G, Backlund, L, Baune, BT, Bellivier, F, Bengesser, S, Berrettini, WH, Blackwood, DHR, Boehnke, M, Borglum, AD, Breen, G, Carr, VJ, Catts, S, Corvin, A, Craddock, N, Dannlowski, U, Dikeos, D, Esko, T, Etain, B, Ferentinos, P, Frye, M, Fullerton, JM, Gawlik, M, Gershon, ES, Goes, F, Green, MJ, Grigoroiu-Serbanescu, M, Hauser, J, Henskens, F, Hillert, J, Hong, KS, Hougaard, DM, Hultman, CM, Hveem, K, Iwata, N, Jablensky, A, Jones, I, Jones, LA, Kahn, RS, Kelsoe, JR, Kirov, G, Landen, M, Leboyer, M, Lewis, CM, Li, QS, Lissowska, J, Lochner, C, Loughland, C, Martin, NG, Mathews, CA, Mayoral, F, McElroy, SL, McIntosh, AM, McMahon, FJ, Melle, I, Michie, P, Milani, L, Mitchell, PB, Morken, G, Mors, O, Mortensen, PB, Mowry, B, Muller-Myhsok, B, Myers, RM, Neale, BM, Nievergelt, CM, Nordentoft, M, Nothen, MM, ODonovan, MC, Oedegaard, KJ, Olsson, T, Owen, MJ, Paciga, SA, Pantelis, C, Pato, C, Pato, MT, Patrinos, GP, Perlis, RH, Posthuma, D, Ramos-Quiroga, JA, Reif, A, Reininghaus, EZ, Ribases, M, Rietschel, M, Ripke, S, Rouleau, GA, Saito, T, Schall, U, Schalling, M, Schofield, PR, Schulze, TG, Scott, LJ, Scott, RJ, Serretti, A, Weickert, CS, Smoller, JW, Stefansson, H, Stefansson, K, Stordal, E, Streit, F, Sullivan, PF, Turecki, G, Vaaler, AE, Vieta, E, Vincent, JB, Waldman, ID, Weickert, TW, Werge, T, Wray, NR, Zwart, J, Biernacka, JM, Nurnberger, J, Cichon, S, Edenberg, HJ, Stahl, EA, McQuillin, A, Di Florio, A, Ophoff, RA, and Andreassen, OA
Abstract: 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.
Published: 2021

25. Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease

Author: Keret, O, Staffaroni, AM, Ringman, JM, Cobigo, Y, Goh, S-YM, Wolf, A, Allen, IE, Salloway, S, Chhatwal, J, Brickman, AM, Reyes-Dumeyer, D, Bateman, RJ, Benzinger, TLS, Morris, JC, Ances, BM, Joseph-Mathurin, N, Perrin, RJ, Gordon, BA, Levin, J, Voeglein, J, Jucker, M, Fougere, C, Martins, RN, Sohrabi, HR, Taddei, K, Villemagne, VL, Schofield, PR, Brooks, WS, Fulham, M, Masters, CL, Ghetti, B, Saykin, AJ, Jack, CR, Graff-Radford, NR, Weiner, M, Cash, DM, Allegri, RF, Chrem, P, Yi, S, Miller, BL, Rabinovici, GD, Rosen, HJ, Keret, O, Staffaroni, AM, Ringman, JM, Cobigo, Y, Goh, S-YM, Wolf, A, Allen, IE, Salloway, S, Chhatwal, J, Brickman, AM, Reyes-Dumeyer, D, Bateman, RJ, Benzinger, TLS, Morris, JC, Ances, BM, Joseph-Mathurin, N, Perrin, RJ, Gordon, BA, Levin, J, Voeglein, J, Jucker, M, Fougere, C, Martins, RN, Sohrabi, HR, Taddei, K, Villemagne, VL, Schofield, PR, Brooks, WS, Fulham, M, Masters, CL, Ghetti, B, Saykin, AJ, Jack, CR, Graff-Radford, NR, Weiner, M, Cash, DM, Allegri, RF, Chrem, P, Yi, S, Miller, BL, Rabinovici, GD, and Rosen, HJ
Abstract: INTRODUCTION: Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment. METHODS: We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally. RESULTS: Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset. DISCUSSION: Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials.
Published: 2021

26. Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group

Author: Jia, T, Chu, C, Liu, Y, van Dongen, J, Papastergios, E, Armstrong, NJ, Bastin, ME, Carrillo-Roa, T, den Braber, A, Harris, M, Jansen, R, Liu, J, Luciano, M, Ori, APS, Santianez, RR, Ruggeri, B, Sarkisyan, D, Shin, J, Sungeun, K, Gutierrez, DT, van't Ent, D, Ames, D, Artiges, E, Bakalkin, G, Banaschewski, T, Bokde, ALW, Brodaty, H, Bromberg, U, Brouwer, R, Buchel, C, Quinlan, EB, Cahn, W, de Zubicaray, G, Ehrlich, S, Ekstrom, TJ, Flor, H, Frohner, JH, Frouin, V, Garavan, H, Gowland, P, Heinz, A, Hoare, J, Ittermann, B, Jahanshad, N, Jiang, J, Kwok, JB, Martin, NG, Martinot, J-L, Mather, KA, McMahon, KL, McRae, AF, Nees, F, Orfanos, DP, Paus, T, Poustka, L, Samann, PG, Schofield, PR, Smolka, MN, Stein, DJ, Strike, LT, Teeuw, J, Thalamuthu, A, Trollor, J, Walter, H, Wardlaw, JM, Wen, W, Whelan, R, Apostolova, LG, Binder, EB, Boomsma, D, Calhoun, V, Crespo-Facorro, B, Deary, IJ, Pol, HH, Ophoff, RA, Pausova, Z, Sachdev, PS, Saykin, A, Wright, MJ, Thompson, PM, Schumann, G, Desrivieres, S, Jia, T, Chu, C, Liu, Y, van Dongen, J, Papastergios, E, Armstrong, NJ, Bastin, ME, Carrillo-Roa, T, den Braber, A, Harris, M, Jansen, R, Liu, J, Luciano, M, Ori, APS, Santianez, RR, Ruggeri, B, Sarkisyan, D, Shin, J, Sungeun, K, Gutierrez, DT, van't Ent, D, Ames, D, Artiges, E, Bakalkin, G, Banaschewski, T, Bokde, ALW, Brodaty, H, Bromberg, U, Brouwer, R, Buchel, C, Quinlan, EB, Cahn, W, de Zubicaray, G, Ehrlich, S, Ekstrom, TJ, Flor, H, Frohner, JH, Frouin, V, Garavan, H, Gowland, P, Heinz, A, Hoare, J, Ittermann, B, Jahanshad, N, Jiang, J, Kwok, JB, Martin, NG, Martinot, J-L, Mather, KA, McMahon, KL, McRae, AF, Nees, F, Orfanos, DP, Paus, T, Poustka, L, Samann, PG, Schofield, PR, Smolka, MN, Stein, DJ, Strike, LT, Teeuw, J, Thalamuthu, A, Trollor, J, Walter, H, Wardlaw, JM, Wen, W, Whelan, R, Apostolova, LG, Binder, EB, Boomsma, D, Calhoun, V, Crespo-Facorro, B, Deary, IJ, Pol, HH, Ophoff, RA, Pausova, Z, Sachdev, PS, Saykin, A, Wright, MJ, Thompson, PM, Schumann, G, and Desrivieres, S
Abstract: DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.
Published: 2021

27. Association of polygenic score for major depression with response to lithium in patients with bipolar disorder

Author: Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Cearns, M, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, Y-H, Shekhtman, T, AdIi, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, K, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Etain, B, Jamain, S, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Koenig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Noethen, MM, Novak, T, O'Donovan, C, Ozaki, N, Osby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Maj, M, Turecki, G, Vieta, E, Veeh, J, Witt, SH, Wright, A, Zandi, PP, Mitchell, PB, Bauer, M, Alda, M, Rietschel, M, McMahon, FJ, Schulze, TG, Baune, BT, Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Cearns, M, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, Y-H, Shekhtman, T, AdIi, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, K, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Etain, B, Jamain, S, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Koenig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Noethen, MM, Novak, T, O'Donovan, C, Ozaki, N, Osby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Maj, M, Turecki, G, Vieta, E, Veeh, J, Witt, SH, Wright, A, Zandi, PP, Mitchell, PB, Bauer, M, Alda, M, Rietschel, M, McMahon, FJ, Schulze, TG, and Baune, BT
Abstract: Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findin
Published: 2021

28. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Author: Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abe, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargallo, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bulow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjo-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Gur, RE, Gur, RC, Haar, S, Haarman, BCM, Haavik, J, Hahn, T, Hajek, T, Harrison, BJ, Harrison, NA, Hartman, CA, Whalley, HC, Heslenfeld, DJ, Hibar, DP, Hilland, E, Hirano, Y, Ho, TC, Hoekstra, PJ, Hoekstra, L, Hohmann, S, Hong, LE, Hoschl, C, Hovik, MF, Howells, FM, Nenadic, I, Jalbrzikowski, M, James, AC, Janssen, J, Jaspers-Fayer, F, Xu, J, Jonassen, R, Karkashadze, G, King, JA, Kircher, T, Kirschner, M, Koch, K, Kochunov, P, Kohls, G, Konrad, K, Kramer, B, Krug, A, Kuntsi, J, Kwon, JS, Landen, M, Landro, NI, Lazaro, L, Lebedeva, IS, Leehr, EJ, Lera-Miguel, S, Lesch, K-P, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Malpas, CB, Portella, MJ, Marsh, R, Martyn, FM, Mataix-Cols, D, Mathalon, DH, McCarthy, H, McDonald, C, McPhilemy, G, Meinert, S, Menchon, JM, Minuzzi, L, Mitchell, PB, Moreno, C, Morgado, P, Muratori, F, Murphy, CM, Murphy, D, Mwangi, B, Nabulsi, L, Nakagawa, A, Nakamae, T, Namazova, L, Narayanaswamy, J, Jahanshad, N, Nguyen, DD, Nicolau, R, O'Gorman Tuura, RL, O'Hearn, K, Oosterlaan, J, Opel, N, Ophoff, RA, Oranje, B, Garcia de la Foz, VO, Overs, BJ, Paloyelis, Y, Pantelis, C, Parellada, M, Pauli, P, Pico-Perez, M, Picon, FA, Piras, F, Plessen, KJ, Pomarol-Clotet, E, Preda, A, Puig, O, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Rauer, L, Reddy, J, Redlich, R, Reif, A, Reneman, L, Repple, J, Retico, A, Richarte, V, Richter, A, Rosa, PGP, Rubia, KK, Hashimoto, R, Sacchet, MD, Salvador, R, Santonja, J, Sarink, K, Sarro, S, Satterthwaite, TD, Sawa, A, Schall, U, Schofield, PR, Schrantee, A, Seitz, J, Serpa, MH, Setien-Suero, E, Shaw, P, Shook, D, Silk, TJ, Sim, K, Simon, S, Simpson, HB, Singh, A, Skoch, A, Skokauskas, N, Soares, JC, Soreni, N, Soriano-Mas, C, Spalletta, G, Spaniel, F, Lawrie, SM, Stern, ER, Stewart, SE, Takayanagi, Y, Temmingh, HS, Tolin, DF, Tomecek, D, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, van Amelsvoort, T, van der Wee, NJA, van der Werff, SJA, van Haren, NEM, van Wingen, GA, Vance, A, Vazquez-Bourgon, J, Vecchio, D, Venkatasubramanian, G, Vieta, E, Vilarroya, O, Vives-Gilabert, Y, Voineskos, AN, Volzke, H, von Polier, GG, Walton, E, Weickert, TW, Weickert, CS, Weideman, AS, Wittfeld, K, Wolf, DH, Wu, M-J, Yang, TT, Yang, K, Yoncheva, Y, Yun, J-Y, Cheng, Y, Zanetti, MV, Ziegler, GC, Franke, B, Hoogman, M, Buitelaar, JK, van Rooij, D, Andreassen, OA, Ching, CRK, Veltman, DJ, Schmaal, L, Stein, DJ, van den Heuvel, OA, Turner, JA, van Erp, TGM, Pausova, Z, Thompson, PM, Paus, T, Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abe, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargallo, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bulow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjo-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Gur, RE, Gur, RC, Haar, S, Haarman, BCM, Haavik, J, Hahn, T, Hajek, T, Harrison, BJ, Harrison, NA, Hartman, CA, Whalley, HC, Heslenfeld, DJ, Hibar, DP, Hilland, E, Hirano, Y, Ho, TC, Hoekstra, PJ, Hoekstra, L, Hohmann, S, Hong, LE, Hoschl, C, Hovik, MF, Howells, FM, Nenadic, I, Jalbrzikowski, M, James, AC, Janssen, J, Jaspers-Fayer, F, Xu, J, Jonassen, R, Karkashadze, G, King, JA, Kircher, T, Kirschner, M, Koch, K, Kochunov, P, Kohls, G, Konrad, K, Kramer, B, Krug, A, Kuntsi, J, Kwon, JS, Landen, M, Landro, NI, Lazaro, L, Lebedeva, IS, Leehr, EJ, Lera-Miguel, S, Lesch, K-P, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Malpas, CB, Portella, MJ, Marsh, R, Martyn, FM, Mataix-Cols, D, Mathalon, DH, McCarthy, H, McDonald, C, McPhilemy, G, Meinert, S, Menchon, JM, Minuzzi, L, Mitchell, PB, Moreno, C, Morgado, P, Muratori, F, Murphy, CM, Murphy, D, Mwangi, B, Nabulsi, L, Nakagawa, A, Nakamae, T, Namazova, L, Narayanaswamy, J, Jahanshad, N, Nguyen, DD, Nicolau, R, O'Gorman Tuura, RL, O'Hearn, K, Oosterlaan, J, Opel, N, Ophoff, RA, Oranje, B, Garcia de la Foz, VO, Overs, BJ, Paloyelis, Y, Pantelis, C, Parellada, M, Pauli, P, Pico-Perez, M, Picon, FA, Piras, F, Plessen, KJ, Pomarol-Clotet, E, Preda, A, Puig, O, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Rauer, L, Reddy, J, Redlich, R, Reif, A, Reneman, L, Repple, J, Retico, A, Richarte, V, Richter, A, Rosa, PGP, Rubia, KK, Hashimoto, R, Sacchet, MD, Salvador, R, Santonja, J, Sarink, K, Sarro, S, Satterthwaite, TD, Sawa, A, Schall, U, Schofield, PR, Schrantee, A, Seitz, J, Serpa, MH, Setien-Suero, E, Shaw, P, Shook, D, Silk, TJ, Sim, K, Simon, S, Simpson, HB, Singh, A, Skoch, A, Skokauskas, N, Soares, JC, Soreni, N, Soriano-Mas, C, Spalletta, G, Spaniel, F, Lawrie, SM, Stern, ER, Stewart, SE, Takayanagi, Y, Temmingh, HS, Tolin, DF, Tomecek, D, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, van Amelsvoort, T, van der Wee, NJA, van der Werff, SJA, van Haren, NEM, van Wingen, GA, Vance, A, Vazquez-Bourgon, J, Vecchio, D, Venkatasubramanian, G, Vieta, E, Vilarroya, O, Vives-Gilabert, Y, Voineskos, AN, Volzke, H, von Polier, GG, Walton, E, Weickert, TW, Weickert, CS, Weideman, AS, Wittfeld, K, Wolf, DH, Wu, M-J, Yang, TT, Yang, K, Yoncheva, Y, Yun, J-Y, Cheng, Y, Zanetti, MV, Ziegler, GC, Franke, B, Hoogman, M, Buitelaar, JK, van Rooij, D, Andreassen, OA, Ching, CRK, Veltman, DJ, Schmaal, L, Stein, DJ, van den Heuvel, OA, Turner, JA, van Erp, TGM, Pausova, Z, Thompson, PM, and Paus, T
Abstract: IMPORTANCE: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. OBJECTIVE: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. MAIN OUTCOMES AND MEASURES: Interregional profiles of group difference in cortical thickness between cases and controls. RESULTS: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene
Published: 2021

29. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Author: Han, LKM, Dinga, R, Hahn, T, Ching, CRK, Eyler, LT, Aftanas, L, Aghajani, M, Aleman, A, Baune, BT, Berger, K, Brak, I, Busatto Filho, G, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, CG, Dima, D, Duran, FLS, Enneking, V, Filimonova, E, Frenzel, S, Frodl, T, Fu, CHY, Godlewska, BR, Gotlib, IH, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Hosten, N, Jansen, A, Kaehler, C, Kircher, T, Klimes-Dougan, B, Kraemer, B, Krug, A, Lagopoulos, J, Leenings, R, MacMaster, FP, MacQueen, G, McIntosh, A, McLellan, Q, McMahon, KL, Medland, SE, Mueller, BA, Mwangi, B, Osipov, E, Portella, MJ, Pozzi, E, Reneman, L, Repple, J, Rosa, PGP, Sacchet, MD, Saemann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinstraeter, O, Strike, LT, Thomopoulos, SI, van Tol, M-J, Veer, IM, Vermeiren, RRJM, Walter, H, van der Wee, NJA, van der Werff, SJA, Whalley, H, Winter, NR, Wittfeld, K, Wright, MJ, Wu, M-J, Voelzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abe, C, Alda, M, Andreassen, OA, Boen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsashagen, T, Favre, P, Foley, SF, Fullerton, JM, Goikolea, JM, Haarman, BCM, Hajek, T, Henry, C, Houenou, J, Howells, FM, Ingvar, M, Kuplicki, R, Lafer, B, Landen, M, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Nabulsi, L, Otaduy, MCG, Overs, BJ, Polosan, M, Pomarol-Clotet, E, Radua, J, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Savitz, J, Schene, AH, Schofield, PR, Serpa, MH, Sim, K, Soeiro-de-Souza, MG, Sutherland, AN, Temmingh, HS, Timmons, GM, Uhlmann, A, Vieta, E, Wolf, DH, Zanetti, MV, Jahanshad, N, Thompson, PM, Veltman, DJ, Penninx, BWJH, Marquand, AF, Cole, JH, Schmaal, L, Han, LKM, Dinga, R, Hahn, T, Ching, CRK, Eyler, LT, Aftanas, L, Aghajani, M, Aleman, A, Baune, BT, Berger, K, Brak, I, Busatto Filho, G, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, CG, Dima, D, Duran, FLS, Enneking, V, Filimonova, E, Frenzel, S, Frodl, T, Fu, CHY, Godlewska, BR, Gotlib, IH, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Hosten, N, Jansen, A, Kaehler, C, Kircher, T, Klimes-Dougan, B, Kraemer, B, Krug, A, Lagopoulos, J, Leenings, R, MacMaster, FP, MacQueen, G, McIntosh, A, McLellan, Q, McMahon, KL, Medland, SE, Mueller, BA, Mwangi, B, Osipov, E, Portella, MJ, Pozzi, E, Reneman, L, Repple, J, Rosa, PGP, Sacchet, MD, Saemann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinstraeter, O, Strike, LT, Thomopoulos, SI, van Tol, M-J, Veer, IM, Vermeiren, RRJM, Walter, H, van der Wee, NJA, van der Werff, SJA, Whalley, H, Winter, NR, Wittfeld, K, Wright, MJ, Wu, M-J, Voelzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abe, C, Alda, M, Andreassen, OA, Boen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsashagen, T, Favre, P, Foley, SF, Fullerton, JM, Goikolea, JM, Haarman, BCM, Hajek, T, Henry, C, Houenou, J, Howells, FM, Ingvar, M, Kuplicki, R, Lafer, B, Landen, M, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Nabulsi, L, Otaduy, MCG, Overs, BJ, Polosan, M, Pomarol-Clotet, E, Radua, J, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Savitz, J, Schene, AH, Schofield, PR, Serpa, MH, Sim, K, Soeiro-de-Souza, MG, Sutherland, AN, Temmingh, HS, Timmons, GM, Uhlmann, A, Vieta, E, Wolf, DH, Zanetti, MV, Jahanshad, N, Thompson, PM, Veltman, DJ, Penninx, BWJH, Marquand, AF, Cole, JH, and Schmaal, L
Abstract: Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.
Published: 2021

30. Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients

Author: Schubert, KO, Thalamuthu, A, Amare, AT, Frank, J, Streit, F, Adl, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Marie-Claire, C, Cearns, M, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Clark, SR, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Etain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Heilbronner, U, Herms, S, Hoffmann, P, Hou, L, Hsu, Y-H, Jamain, S, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, J, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, Koenig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Noethen, MM, Novak, T, O'Donovan, C, Ozaki, N, Oesby, U, Papiol, S, Pfennig, A, Pisanu, C, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Tekola-Ayele, F, Tortorella, A, Turecki, G, Veeh, J, Vieta, E, Witt, SH, Roberts, G, Zandi, PP, Alda, M, Bauer, M, McMahon, FJ, Mitchell, PB, Schulze, TG, Rietschel, M, Baune, BT, Schubert, KO, Thalamuthu, A, Amare, AT, Frank, J, Streit, F, Adl, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Marie-Claire, C, Cearns, M, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Clark, SR, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Etain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Heilbronner, U, Herms, S, Hoffmann, P, Hou, L, Hsu, Y-H, Jamain, S, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, J, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, Koenig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Noethen, MM, Novak, T, O'Donovan, C, Ozaki, N, Oesby, U, Papiol, S, Pfennig, A, Pisanu, C, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Tekola-Ayele, F, Tortorella, A, Turecki, G, Veeh, J, Vieta, E, Witt, SH, Roberts, G, Zandi, PP, Alda, M, Bauer, M, McMahon, FJ, Mitchell, PB, Schulze, TG, Rietschel, M, and Baune, BT
Abstract: Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.
Published: 2021

31. Electroencephalography profiles as a biomarker of wellbeing: A twin study

Author: Chilver, MR, Keller, AS, Park, HRP, Jamshidi, J, Montalto, A, Schofield, PR, Clark, CR, Harmon-Jones, E, Williams, LM, Gatt, JM, Chilver, MR, Keller, AS, Park, HRP, Jamshidi, J, Montalto, A, Schofield, PR, Clark, CR, Harmon-Jones, E, Williams, LM, and Gatt, JM
Abstract: Alterations to electroencephalography (EEG) power have been reported for psychiatric conditions such as depression and anxiety, but not for mental wellbeing in a healthy population. This study examined the resting EEG profiles associated with mental wellbeing, and how genetics and environment contribute to these associations using twin modelling. Mental wellbeing was assessed using the COMPAS-W Wellbeing Scale which measures both subjective and psychological wellbeing. In 422 healthy adult monozygotic and dizygotic twins aged 18–61 years, we examined the association between mental wellbeing and EEG power (alpha, beta, theta, delta) using linear mixed models. This was followed by univariate and multivariate twin modelling to assess the heritability of wellbeing and EEG power, and whether the association was driven by shared genetics or environment. A significant association between wellbeing and an interaction of alpha, beta, and delta (ABD) power was found (β = −0.33, p < 0.001) whereby a profile of high alpha and delta and low beta was associated with higher wellbeing, independent of depression and anxiety symptoms. This finding was supported by a five-fold cross-validation analysis. A significant genetic correlation (rG = −0.43) was found to account for 94% of the association between wellbeing and the EEG power interaction. Together, this study has identified a novel EEG profile with a common genetic component that may be a potential biomarker of mental wellbeing. Future studies need to clarify the causal direction of this association.
Published: 2020

32. Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults

Author: Hofer, E, Roshchupkin, GV, Adams, HHH, Knol, MJ, Lin, H, Li, S, Zare, H, Ahmad, S, Armstrong, NJ, Satizabal, CL, Bernard, M, Bis, JC, Gillespie, NA, Luciano, M, Mishra, A, Scholz, M, Teumer, A, Xia, R, Jian, X, Mosley, TH, Saba, Y, Pirpamer, L, Seiler, S, Becker, JT, Carmichael, O, Rotter, JI, Psaty, BM, Lopez, OL, Amin, N, van der Lee, SJ, Yang, Q, Himali, JJ, Maillard, P, Beiser, AS, Decarli, C, Karama, S, Lewis, L, Harris, M, Bastin, ME, Deary, IJ, Witte, AV, Beyer, F, Loeffler, M, Mather, KA, Schofield, PR, Thalamuthu, A, Kwok, JB, Wright, MJ, Ames, D, Trollor, J, Jiang, J, Brodaty, H, Wen, W, Vernooij, MW, Hofman, A, Uitterlinden, AG, Niessen, WJ, Wittfeld, K, Bülow, R, Völker, U, Pausova, Z, Pike, GB, Maingault, S, Crivello, F, Tzourio, C, Amouyel, P, Mazoyer, B, Neale, MC, Franz, CE, Lyons, MJ, Panizzon, MS, Andreassen, OA, Dale, AM, Logue, M, Grasby, KL, Jahanshad, N, Painter, JN, Colodro-Conde, L, Bralten, J, Hibar, DP, Lind, PA, Pizzagalli, F, Stein, JL, Thompson, PM, Medland, SE, Sachdev, PS, Kremen, WS, Wardlaw, JM, Villringer, A, van Duijn, CM, Grabe, HJ, Longstreth, WT, Fornage, M, Paus, T, Debette, S, Ikram, MA, Schmidt, H, Schmidt, R, Seshadri, S, Ching, CRK, Hofer, E, Roshchupkin, GV, Adams, HHH, Knol, MJ, Lin, H, Li, S, Zare, H, Ahmad, S, Armstrong, NJ, Satizabal, CL, Bernard, M, Bis, JC, Gillespie, NA, Luciano, M, Mishra, A, Scholz, M, Teumer, A, Xia, R, Jian, X, Mosley, TH, Saba, Y, Pirpamer, L, Seiler, S, Becker, JT, Carmichael, O, Rotter, JI, Psaty, BM, Lopez, OL, Amin, N, van der Lee, SJ, Yang, Q, Himali, JJ, Maillard, P, Beiser, AS, Decarli, C, Karama, S, Lewis, L, Harris, M, Bastin, ME, Deary, IJ, Witte, AV, Beyer, F, Loeffler, M, Mather, KA, Schofield, PR, Thalamuthu, A, Kwok, JB, Wright, MJ, Ames, D, Trollor, J, Jiang, J, Brodaty, H, Wen, W, Vernooij, MW, Hofman, A, Uitterlinden, AG, Niessen, WJ, Wittfeld, K, Bülow, R, Völker, U, Pausova, Z, Pike, GB, Maingault, S, Crivello, F, Tzourio, C, Amouyel, P, Mazoyer, B, Neale, MC, Franz, CE, Lyons, MJ, Panizzon, MS, Andreassen, OA, Dale, AM, Logue, M, Grasby, KL, Jahanshad, N, Painter, JN, Colodro-Conde, L, Bralten, J, Hibar, DP, Lind, PA, Pizzagalli, F, Stein, JL, Thompson, PM, Medland, SE, Sachdev, PS, Kremen, WS, Wardlaw, JM, Villringer, A, van Duijn, CM, Grabe, HJ, Longstreth, WT, Fornage, M, Paus, T, Debette, S, Ikram, MA, Schmidt, H, Schmidt, R, Seshadri, S, and Ching, CRK
Abstract: Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.
Published: 2020

33. Cerebral small vessel disease genomics and its implications across the lifespan

Author: Sargurupremraj, M, Suzuki, H, Jian, X, Sarnowski, C, Evans, TE, Bis, JC, Eiriksdottir, G, Sakaue, S, Terzikhan, N, Habes, M, Zhao, W, Armstrong, NJ, Hofer, E, Yanek, LR, Hagenaars, SP, Kumar, RB, van den Akker, EB, McWhirter, RE, Trompet, S, Mishra, A, Saba, Y, Satizabal, CL, Beaudet, G, Petit, L, Tsuchida, A, Zago, L, Schilling, S, Sigurdsson, S, Gottesman, RF, Lewis, CE, Aggarwal, NT, Lopez, OL, Smith, JA, Valdés Hernández, MC, van der Grond, J, Wright, MJ, Knol, MJ, Dörr, M, Thomson, RJ, Bordes, C, Le Grand, Q, Duperron, MG, Smith, AV, Knopman, DS, Schreiner, PJ, Evans, DA, Rotter, JI, Beiser, AS, Maniega, SM, Beekman, M, Trollor, J, Stott, DJ, Vernooij, MW, Wittfeld, K, Niessen, WJ, Soumaré, A, Boerwinkle, E, Sidney, S, Turner, ST, Davies, G, Thalamuthu, A, Völker, U, van Buchem, MA, Bryan, RN, Dupuis, J, Bastin, ME, Ames, D, Teumer, A, Amouyel, P, Kwok, JB, Bülow, R, Deary, IJ, Schofield, PR, Brodaty, H, Jiang, J, Tabara, Y, Setoh, K, Miyamoto, S, Yoshida, K, Nagata, M, Kamatani, Y, Matsuda, F, Psaty, BM, Bennett, DA, De Jager, PL, Mosley, TH, Sachdev, PS, Schmidt, R, Warren, HR, Evangelou, E, Trégouët, DA, de Andrade, M, Basu, S, Berr, C, Brody, JA, Chasman, DI, Dartigues, JF, Folsom, AR, Germain, M, Sargurupremraj, M, Suzuki, H, Jian, X, Sarnowski, C, Evans, TE, Bis, JC, Eiriksdottir, G, Sakaue, S, Terzikhan, N, Habes, M, Zhao, W, Armstrong, NJ, Hofer, E, Yanek, LR, Hagenaars, SP, Kumar, RB, van den Akker, EB, McWhirter, RE, Trompet, S, Mishra, A, Saba, Y, Satizabal, CL, Beaudet, G, Petit, L, Tsuchida, A, Zago, L, Schilling, S, Sigurdsson, S, Gottesman, RF, Lewis, CE, Aggarwal, NT, Lopez, OL, Smith, JA, Valdés Hernández, MC, van der Grond, J, Wright, MJ, Knol, MJ, Dörr, M, Thomson, RJ, Bordes, C, Le Grand, Q, Duperron, MG, Smith, AV, Knopman, DS, Schreiner, PJ, Evans, DA, Rotter, JI, Beiser, AS, Maniega, SM, Beekman, M, Trollor, J, Stott, DJ, Vernooij, MW, Wittfeld, K, Niessen, WJ, Soumaré, A, Boerwinkle, E, Sidney, S, Turner, ST, Davies, G, Thalamuthu, A, Völker, U, van Buchem, MA, Bryan, RN, Dupuis, J, Bastin, ME, Ames, D, Teumer, A, Amouyel, P, Kwok, JB, Bülow, R, Deary, IJ, Schofield, PR, Brodaty, H, Jiang, J, Tabara, Y, Setoh, K, Miyamoto, S, Yoshida, K, Nagata, M, Kamatani, Y, Matsuda, F, Psaty, BM, Bennett, DA, De Jager, PL, Mosley, TH, Sachdev, PS, Schmidt, R, Warren, HR, Evangelou, E, Trégouët, DA, de Andrade, M, Basu, S, Berr, C, Brody, JA, Chasman, DI, Dartigues, JF, Folsom, AR, and Germain, M
Abstract: White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.
Published: 2020

34. Erratum: A Neuroethics Framework for the Australian Brain Initiative (Neuron (2019) 101(3) (365–369), (S0896627319300054), (10.1016/j.neuron.2019.01.004))

Author: Carter, A, Richards, LJ, Apthorp, D, Azghadi, MR, Badcock, DR, Balleine, B, Bekkers, JM, Berk, M, Bourne, JA, Bradley, AP, Breakspear, M, Brichta, A, Carter, O, Castles, A, Chakli, K, Cohen-Woods, S, Conn, SJ, Cornish, J, Cornish, K, de Zubicaray, G, Egan, GF, Enticott, PG, Fitzgibbon, BM, Forlini, C, Fornito, A, Griffiths, L, Gullifer, J, Hall, W, Halliday, G, Hannan, AJ, Harrer, S, Harvey, A, Hatherly, C, Hickie, IB, Kennett, J, Kiernan, M, Kilpatrick, T, Kiral-Kornek, I, Korgaonkar, MS, Lawrence, AJ, Leventer, R, Levy, N, Licinio, J, Lovell, N, Mackellar, G, Malcolm, L, Mason, A, Mattingley, JB, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Poole-Warren, L, Sah, P, Sarnyai, Z, Schofield, PR, Shimoni, O, Shum, DHK, Silk, T, Slee, M, Smith, AE, Soulis, T, Sriram, S, Stuart, GJ, Tapson, J, Thompson, MB, van Schaik, A, Vincent, NA, Vissel, B, Waters, A, Carter, A, Richards, LJ, Apthorp, D, Azghadi, MR, Badcock, DR, Balleine, B, Bekkers, JM, Berk, M, Bourne, JA, Bradley, AP, Breakspear, M, Brichta, A, Carter, O, Castles, A, Chakli, K, Cohen-Woods, S, Conn, SJ, Cornish, J, Cornish, K, de Zubicaray, G, Egan, GF, Enticott, PG, Fitzgibbon, BM, Forlini, C, Fornito, A, Griffiths, L, Gullifer, J, Hall, W, Halliday, G, Hannan, AJ, Harrer, S, Harvey, A, Hatherly, C, Hickie, IB, Kennett, J, Kiernan, M, Kilpatrick, T, Kiral-Kornek, I, Korgaonkar, MS, Lawrence, AJ, Leventer, R, Levy, N, Licinio, J, Lovell, N, Mackellar, G, Malcolm, L, Mason, A, Mattingley, JB, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Poole-Warren, L, Sah, P, Sarnyai, Z, Schofield, PR, Shimoni, O, Shum, DHK, Silk, T, Slee, M, Smith, AE, Soulis, T, Sriram, S, Stuart, GJ, Tapson, J, Thompson, MB, van Schaik, A, Vincent, NA, Vissel, B, and Waters, A
Abstract: (Neuron 101, 365–369; February 6, 2019) In the original publication of this NeuroView, the member list for the Australian Brain Alliance was omitted. This has now been corrected online. Neuron apologizes for the error.
Published: 2020

35. Psychosocial implications of living with familial risk of a psychiatric disorder and attitudes to psychiatric genetic testing: A systematic review of the literature

Author: Meiser, B, Guo, XY, Putt, S, Fullerton, JM, Schofield, PR, Mitchell, PB, Yanes, T, Meiser, B, Guo, XY, Putt, S, Fullerton, JM, Schofield, PR, Mitchell, PB, and Yanes, T
Abstract: The aim of this systematic review was to synthesize the existing evidence documenting the psychosocial implications of living with a familial risk of an adult-onset psychiatric disorder. Six databases were searched systematically to identify qualitative and quantitative studies, which explored perspectives of those at increased risk for psychiatric disorders, as well as the general public. Thematic analysis was used to identify major themes. Thirty-five articles met the eligibility criteria and reported on the views of 4,896 participants. The literature demonstrates strong interest in psychiatric genetic testing of adults as well as children, whereas attitudes toward prenatal testing were much less positive. Predictors of interest in testing, as well as perceived advantages and disadvantages were identified. Very few studies are available on anticipated and actual reactions to receiving results. Studies show that the majority of participants feel that having a genetic explanation would alleviate some of the stigma associated with mental illness. This review shows that interest in, and predictors of attitudes toward, psychiatric genetic testing are well researched, but the extent to which attitudes will translate into actual testing uptake is unknown. Future research also needs to assess the actual behavioral and psychological impact of genetic testing.
Published: 2020

36. Exploration of experiences with and understanding of polygenic risk scores for bipolar disorder

Author: Putt, S, Yanes, T, Meiser, B, Kaur, R, Fullerton, JM, Barlow-Stewart, K, Schofield, PR, Toma, C, Peay, H, Mitchell, PB, Putt, S, Yanes, T, Meiser, B, Kaur, R, Fullerton, JM, Barlow-Stewart, K, Schofield, PR, Toma, C, Peay, H, and Mitchell, PB
Abstract: Background: Polygenic risk scores (PRSs) summarise genetic risk in complex genetic disorders such as bipolar disorder (BD). The aim of this study was to gain in-depth, nuanced information regarding the understanding and experience of receiving a PRS for BD from individuals who already have a BD diagnosis. Methods: Participants from a previous genetics study were invited to receive their PRS in a face-to-face consultation with a genetic counsellor or psychiatrist. Four weeks later, semi-structured interviews were conducted, with 14 ‘acceptors’ (those who chose to receive their PRS) and 4 ‘decliners’ (those who did not wish to receive their PRS). Results: Four themes were developed: (1) An easy decision, (2) A positive experience, (3) The grey area, and (4) The future is exciting and frightening. Despite some reported initial shock and distress, all acceptors described the experience of receiving their PRS as a positive one. It allowed them to better understand their condition and/or reduced feelings of self-blame. Decliners chose not to receive their results because of a lack of perceived usefulness or concern that PRS may hinder personal recovery. Limitations: Given the qualitative design of the study, statistically valid generalisations cannot be undertaken, nor can causal relationships be established. Conclusions: PRS for BD were generally well accepted and understood. Knowledge regarding the impact of PRS for BD ensures that counselling frameworks are responsive to patient needs as well as informing education for psychiatrists and genetic counsellors, who will play pivotal roles in future polygenic testing provision.
Published: 2020

37. Correction : A Neuroethics Framework for the Australian Brain Initiative (Neuron (2019) 101(3) (365–369), (S0896627319300054), (10.1016/j.neuron.2019.01.004))

Author: Carter, Adrian, Richards, Linda J., Apthorp, D, Azghadi, MR, Badcock, DR, Balleine, B, Bekkers, JM, Berk, Michael, Bourne, JA, Bradley, AP, Breakspear, M, Brichta, A, Carter, O, Castles, A, Chakli, K, Cohen-Woods, S, Conn, SJ, Cornish, J, Cornish, K, de Zubicaray, G, Egan, GF, Enticott, Peter, Fitzgibbon, BM, Forlini, Cynthia, Fornito, A, Griffiths, L, Gullifer, J, Hall, W, Halliday, G, Hannan, AJ, Harrer, S, Harvey, A, Hatherly, C, Hickie, IB, Kennett, J, Kiernan, M, Kilpatrick, T, Kiral-Kornek, I, Korgaonkar, MS, Lawrence, Andrew J, Leventer, R, Levy, N, Licinio, J, Lovell, N, Mackellar, G, Malcolm, L, Mason, A, Mattingley, JB, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Poole-Warren, L, Sah, P, Sarnyai, Z, Schofield, PR, Shimoni, O, Shum, DHK, Silk, Timothy, Slee, M, Smith, AE, Soulis, T, Sriram, S, Stuart, GJ, Tapson, J, Thompson, MB, van Schaik, A, Vincent, NA, Vissel, B, Waters, A, Carter, Adrian, Richards, Linda J., Apthorp, D, Azghadi, MR, Badcock, DR, Balleine, B, Bekkers, JM, Berk, Michael, Bourne, JA, Bradley, AP, Breakspear, M, Brichta, A, Carter, O, Castles, A, Chakli, K, Cohen-Woods, S, Conn, SJ, Cornish, J, Cornish, K, de Zubicaray, G, Egan, GF, Enticott, Peter, Fitzgibbon, BM, Forlini, Cynthia, Fornito, A, Griffiths, L, Gullifer, J, Hall, W, Halliday, G, Hannan, AJ, Harrer, S, Harvey, A, Hatherly, C, Hickie, IB, Kennett, J, Kiernan, M, Kilpatrick, T, Kiral-Kornek, I, Korgaonkar, MS, Lawrence, Andrew J, Leventer, R, Levy, N, Licinio, J, Lovell, N, Mackellar, G, Malcolm, L, Mason, A, Mattingley, JB, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Poole-Warren, L, Sah, P, Sarnyai, Z, Schofield, PR, Shimoni, O, Shum, DHK, Silk, Timothy, Slee, M, Smith, AE, Soulis, T, Sriram, S, Stuart, GJ, Tapson, J, Thompson, MB, van Schaik, A, Vincent, NA, Vissel, B, and Waters, A
Published: 2020

38. Global and Regional Development of the Human Cerebral Cortex: Molecular Architecture and Occupational Aptitudes

Author: Shin, J, Ma, S, Hofer, E, Patel, Y, Vosberg, DE, Tilley, S, Roshchupkin, G, Sousa, AMM, Jian, X, Gottesman, R, Mosley, TH, Fornage, M, Saba, Y, Pirpamer, L, Schmidt, R, Schmidt, H, Carrion-Castillo, A, Crivello, F, Mazoyer, B, Bis, JC, Li, S, Yang, Q, Luciano, M, Karama, S, Lewis, L, Bastin, ME, Harris, MA, Wardlaw, JM, Deary, IE, Scholz, M, Loeffler, M, Witte, AV, Beyer, F, Villringer, A, Armstrong, NJ, Mather, KA, Ames, D, Jiang, J, Kwok, JB, Schofield, PR, Thalamuthu, A, Trollor, JN, Wright, MJ, Brodaty, H, Wen, W, Sachdev, PS, Terzikhan, N, Evans, TE, Adams, HHHH, Ikram, MA, Frenzel, S, Van der Auwera-Palitschka, S, Wittfeld, K, Bulow, R, Grabe, HJ, Tzourio, C, Mishra, A, Maingault, S, Debette, S, Gillespie, NA, Franz, CE, Kremen, WS, Ding, L, Jahanshad, N, Sestan, N, Pausova, Z, Seshadri, S, Paus, T, Shin, J, Ma, S, Hofer, E, Patel, Y, Vosberg, DE, Tilley, S, Roshchupkin, G, Sousa, AMM, Jian, X, Gottesman, R, Mosley, TH, Fornage, M, Saba, Y, Pirpamer, L, Schmidt, R, Schmidt, H, Carrion-Castillo, A, Crivello, F, Mazoyer, B, Bis, JC, Li, S, Yang, Q, Luciano, M, Karama, S, Lewis, L, Bastin, ME, Harris, MA, Wardlaw, JM, Deary, IE, Scholz, M, Loeffler, M, Witte, AV, Beyer, F, Villringer, A, Armstrong, NJ, Mather, KA, Ames, D, Jiang, J, Kwok, JB, Schofield, PR, Thalamuthu, A, Trollor, JN, Wright, MJ, Brodaty, H, Wen, W, Sachdev, PS, Terzikhan, N, Evans, TE, Adams, HHHH, Ikram, MA, Frenzel, S, Van der Auwera-Palitschka, S, Wittfeld, K, Bulow, R, Grabe, HJ, Tzourio, C, Mishra, A, Maingault, S, Debette, S, Gillespie, NA, Franz, CE, Kremen, WS, Ding, L, Jahanshad, N, Sestan, N, Pausova, Z, Seshadri, S, and Paus, T
Abstract: We have carried out meta-analyses of genome-wide association studies (GWAS) (n = 23 784) of the first two principal components (PCs) that group together cortical regions with shared variance in their surface area. PC1 (global) captured variations of most regions, whereas PC2 (visual) was specific to the primary and secondary visual cortices. We identified a total of 18 (PC1) and 17 (PC2) independent loci, which were replicated in another 25 746 individuals. The loci of the global PC1 included those associated previously with intracranial volume and/or general cognitive function, such as MAPT and IGF2BP1. The loci of the visual PC2 included DAAM1, a key player in the planar-cell-polarity pathway. We then tested associations with occupational aptitudes and, as predicted, found that the global PC1 was associated with General Learning Ability, and the visual PC2 was associated with the Form Perception aptitude. These results suggest that interindividual variations in global and regional development of the human cerebral cortex (and its molecular architecture) cascade-albeit in a very limited manner-to behaviors as complex as the choice of one's occupation.
Published: 2020

39. Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease

Author: Dincer, A, Gordon, BA, Hari-Raj, A, Keefe, SJ, Flores, S, McKay, NS, Paulick, AM, Lewis, KES, Feldman, RL, Hornbeck, RC, Allegri, R, Ances, BM, Berman, SB, Brickman, AM, Brooks, WS, Cash, DM, Chhatwal, JP, Farlow, MR, la Fougere, C, Fox, NC, Fulham, MJ, Jack, CR, Joseph-Mathurin, N, Karch, CM, Lee, A, Levin, J, Masters, CL, McDade, EM, Oh, H, Perrin, RJ, Raji, C, Salloway, SP, Schofield, PR, Su, Y, Villemagne, VL, Wang, Q, Weiner, MW, Xiong, C, Yakushev, I, Morris, JC, Bateman, RJ, Benzinger, TLS, Dincer, A, Gordon, BA, Hari-Raj, A, Keefe, SJ, Flores, S, McKay, NS, Paulick, AM, Lewis, KES, Feldman, RL, Hornbeck, RC, Allegri, R, Ances, BM, Berman, SB, Brickman, AM, Brooks, WS, Cash, DM, Chhatwal, JP, Farlow, MR, la Fougere, C, Fox, NC, Fulham, MJ, Jack, CR, Joseph-Mathurin, N, Karch, CM, Lee, A, Levin, J, Masters, CL, McDade, EM, Oh, H, Perrin, RJ, Raji, C, Salloway, SP, Schofield, PR, Su, Y, Villemagne, VL, Wang, Q, Weiner, MW, Xiong, C, Yakushev, I, Morris, JC, Bateman, RJ, and Benzinger, TLS
Abstract: Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels
Published: 2020

40. The genetic architecture of the human cerebral cortex

Author: Grasby, KL, Jahanshad, N, Painter, JN, Colodro-Conde, L, Bralten, J, Hibar, DP, Lind, PA, Pizzagalli, F, Ching, CRK, McMahon, MAB, Shatokhina, N, Zsembik, LCP, Thomopoulos, SI, Zhu, AH, Strike, LT, Agartz, I, Alhusaini, S, Almeida, MAA, Alnaes, D, Amlien, IK, Andersson, M, Ard, T, Armstrong, NJ, Ashley-Koch, A, Atkins, JR, Bernard, M, Brouwer, RM, Buimer, EEL, Bulow, R, Burger, C, Cannon, DM, Chakravarty, M, Chen, Q, Cheung, JW, Couvy-Duchesne, B, Dale, AM, Dalvie, S, de Araujo, TK, de Zubicaray, GI, de Zwarte, SMC, den Braber, A, Nhat, TD, Dohm, K, Ehrlich, S, Engelbrecht, H-R, Erk, S, Fan, CC, Fedko, IO, Foley, SF, Ford, JM, Fukunaga, M, Garrett, ME, Ge, T, Giddaluru, S, Goldman, AL, Green, MJ, Groenewold, NA, Grotegerd, D, Gurholt, TP, Gutman, BA, Hansell, NK, Harris, MA, Harrison, MB, Haswell, CC, Hauser, M, Herms, S, Heslenfeld, DJ, Ho, NF, Hoehn, D, Hoffmann, P, Holleran, L, Hoogman, M, Hottenga, J-J, Ikeda, M, Janowitz, D, Jansen, IE, Jia, T, Jockwitz, C, Kanai, R, Karama, S, Kasperaviciute, D, Kaufmann, T, Kelly, S, Kikuchi, M, Klein, M, Knapp, M, Knodt, AR, Kramer, B, Lam, M, Lancaster, TM, Lee, PH, Lett, TA, Lewis, LB, Lopes-Cendes, I, Luciano, M, Macciardi, F, Marquand, AF, Mathias, SR, Melzer, TR, Milaneschi, Y, Mirza-Schreiber, N, Moreira, JCV, Muhleisen, TW, Mueller-Myhsok, B, Najt, P, Nakahara, S, Nho, K, Loohuis, LMO, Orfanos, DP, Pearson, JF, Pitcher, TL, Putz, B, Quide, Y, Ragothaman, A, Rashid, FM, Reay, WR, Redlich, R, Reinbold, CS, Repple, J, Richard, G, Riedel, BC, Risacher, SL, Rocha, CS, Mota, NR, Salminen, L, Saremi, A, Saykin, AJ, Schlag, F, Schmaal, L, Schofield, PR, Secolin, R, Shapland, CY, Shen, L, Shin, J, Shumskaya, E, Sonderby, IE, Sprooten, E, Tansey, KE, Teumer, A, Thalamuthu, A, Tordesillas-Gutierrez, D, Turner, JA, Uhlmann, A, Vallerga, CL, van der Meer, D, van Donkelaar, MMJ, van Eijk, L, van Erp, TGM, van Haren, NEM, van Rooij, D, van Tol, M-J, Veldink, JH, Verhoef, E, Walton, E, Wang, M, Wang, Y, Wardlaw, JM, Wen, W, Westlye, LT, Whelan, CD, Witt, SH, Wittfeld, K, Wolf, C, Wolfers, T, Wu, JQ, Yasuda, CL, Zaremba, D, Zhang, Z, Zwiers, MP, Artiges, E, Assareh, AA, Ayesa-Arriola, R, Belger, A, Brandt, CL, Brown, GG, Cichon, S, Curran, JE, Davies, GE, Degenhardt, F, Dennis, MF, Dietsche, B, Djurovic, S, Doherty, CP, Espiritu, R, Garijo, D, Gil, Y, Gowland, PA, Green, RC, Hausler, AN, Heindel, W, Ho, B-C, Hoffmann, WU, Holsboer, F, Homuth, G, Hosten, N, Jack, CR, Jang, M, Jansen, A, Kimbrel, NA, Kolskar, K, Koops, S, Krug, A, Lim, KO, Luykx, JJ, Mathalon, DH, Mather, KA, Mattay, VS, Matthews, S, Van Son, JM, McEwen, SC, Melle, I, Morris, DW, Mueller, BA, Nauck, M, Nordvik, JE, Noethen, MM, O'Leary, DS, Opel, N, Martinot, M-LP, Pike, GB, Preda, A, Quinlan, EB, Rasser, PE, Ratnakar, V, Reppermund, S, Steen, VM, Tooney, PA, Torres, FR, Veltman, DJ, Voyvodic, JT, Whelan, R, White, T, Yamamori, H, Adams, HHH, Bis, JC, Debette, S, Decarli, C, Fornage, M, Gudnason, V, Hofer, E, Ikram, MA, Launer, L, Longstreth, WT, Lopez, OL, Mazoyer, B, Mosley, TH, Roshchupkin, GV, Satizabal, CL, Schmidt, R, Seshadri, S, Yang, Q, Alvim, MKM, Ames, D, Anderson, TJ, Andreassen, OA, Arias-Vasquez, A, Bastin, ME, Baune, BT, Beckham, JC, Blangero, J, Boomsma, DI, Brodaty, H, Brunner, HG, Buckner, RL, Buitelaar, JK, Bustillo, JR, Cahn, W, Cairns, MJ, Calhoun, V, Carr, VJ, Caseras, X, Caspers, S, Cavalleri, GL, Cendes, F, Corvin, A, Crespo-Facorro, B, Dalrymple-Alford, JC, Dannlowski, U, de Geus, EJC, Deary, IJ, Delanty, N, Depondt, C, Desrivieres, S, Donohoe, G, Espeseth, T, Fernandez, G, Fisher, SE, Flor, H, Forstner, AJ, Francks, C, Franke, B, Glahn, DC, Gollub, RL, Grabe, HJ, Gruber, O, Haberg, AK, Hariri, AR, Hartman, CA, Hashimoto, R, Heinz, A, Henskens, FA, Hillegers, MHJ, Hoekstra, PJ, Holmes, AJ, Hong, LE, Hopkins, WD, Pol, HEH, Jernigan, TL, Jonsson, EG, Kahn, RS, Kennedy, MA, Kircher, TTJ, Kochunov, P, Kwok, JBJ, Le Hellard, S, Loughland, CM, Martin, NG, Martinot, J-L, McDonald, C, McMahon, KL, Meyer-Lindenberg, A, Michie, PT, Morey, RA, Mowry, B, Nyberg, L, Oosterlaan, J, Ophoff, RA, Pantelis, C, Paus, T, Pausova, Z, Penninx, BWJH, Polderman, TJC, Posthuma, D, Rietschel, M, Roffman, JL, Rowland, LM, Sachdev, PS, Samann, PG, Schall, U, Schumann, G, Scott, RJ, Sim, K, Sisodiya, SM, Smoller, JW, Sommer, IE, St Pourcain, B, Stein, DJ, Toga, AW, Trollor, JN, Van der Wee, NJA, van't Ent, D, Volzke, H, Walter, H, Weber, B, Weinberger, DR, Wright, MJ, Zhou, J, Stein, JL, Thompson, PM, Medland, SE, Grasby, KL, Jahanshad, N, Painter, JN, Colodro-Conde, L, Bralten, J, Hibar, DP, Lind, PA, Pizzagalli, F, Ching, CRK, McMahon, MAB, Shatokhina, N, Zsembik, LCP, Thomopoulos, SI, Zhu, AH, Strike, LT, Agartz, I, Alhusaini, S, Almeida, MAA, Alnaes, D, Amlien, IK, Andersson, M, Ard, T, Armstrong, NJ, Ashley-Koch, A, Atkins, JR, Bernard, M, Brouwer, RM, Buimer, EEL, Bulow, R, Burger, C, Cannon, DM, Chakravarty, M, Chen, Q, Cheung, JW, Couvy-Duchesne, B, Dale, AM, Dalvie, S, de Araujo, TK, de Zubicaray, GI, de Zwarte, SMC, den Braber, A, Nhat, TD, Dohm, K, Ehrlich, S, Engelbrecht, H-R, Erk, S, Fan, CC, Fedko, IO, Foley, SF, Ford, JM, Fukunaga, M, Garrett, ME, Ge, T, Giddaluru, S, Goldman, AL, Green, MJ, Groenewold, NA, Grotegerd, D, Gurholt, TP, Gutman, BA, Hansell, NK, Harris, MA, Harrison, MB, Haswell, CC, Hauser, M, Herms, S, Heslenfeld, DJ, Ho, NF, Hoehn, D, Hoffmann, P, Holleran, L, Hoogman, M, Hottenga, J-J, Ikeda, M, Janowitz, D, Jansen, IE, Jia, T, Jockwitz, C, Kanai, R, Karama, S, Kasperaviciute, D, Kaufmann, T, Kelly, S, Kikuchi, M, Klein, M, Knapp, M, Knodt, AR, Kramer, B, Lam, M, Lancaster, TM, Lee, PH, Lett, TA, Lewis, LB, Lopes-Cendes, I, Luciano, M, Macciardi, F, Marquand, AF, Mathias, SR, Melzer, TR, Milaneschi, Y, Mirza-Schreiber, N, Moreira, JCV, Muhleisen, TW, Mueller-Myhsok, B, Najt, P, Nakahara, S, Nho, K, Loohuis, LMO, Orfanos, DP, Pearson, JF, Pitcher, TL, Putz, B, Quide, Y, Ragothaman, A, Rashid, FM, Reay, WR, Redlich, R, Reinbold, CS, Repple, J, Richard, G, Riedel, BC, Risacher, SL, Rocha, CS, Mota, NR, Salminen, L, Saremi, A, Saykin, AJ, Schlag, F, Schmaal, L, Schofield, PR, Secolin, R, Shapland, CY, Shen, L, Shin, J, Shumskaya, E, Sonderby, IE, Sprooten, E, Tansey, KE, Teumer, A, Thalamuthu, A, Tordesillas-Gutierrez, D, Turner, JA, Uhlmann, A, Vallerga, CL, van der Meer, D, van Donkelaar, MMJ, van Eijk, L, van Erp, TGM, van Haren, NEM, van Rooij, D, van Tol, M-J, Veldink, JH, Verhoef, E, Walton, E, Wang, M, Wang, Y, Wardlaw, JM, Wen, W, Westlye, LT, Whelan, CD, Witt, SH, Wittfeld, K, Wolf, C, Wolfers, T, Wu, JQ, Yasuda, CL, Zaremba, D, Zhang, Z, Zwiers, MP, Artiges, E, Assareh, AA, Ayesa-Arriola, R, Belger, A, Brandt, CL, Brown, GG, Cichon, S, Curran, JE, Davies, GE, Degenhardt, F, Dennis, MF, Dietsche, B, Djurovic, S, Doherty, CP, Espiritu, R, Garijo, D, Gil, Y, Gowland, PA, Green, RC, Hausler, AN, Heindel, W, Ho, B-C, Hoffmann, WU, Holsboer, F, Homuth, G, Hosten, N, Jack, CR, Jang, M, Jansen, A, Kimbrel, NA, Kolskar, K, Koops, S, Krug, A, Lim, KO, Luykx, JJ, Mathalon, DH, Mather, KA, Mattay, VS, Matthews, S, Van Son, JM, McEwen, SC, Melle, I, Morris, DW, Mueller, BA, Nauck, M, Nordvik, JE, Noethen, MM, O'Leary, DS, Opel, N, Martinot, M-LP, Pike, GB, Preda, A, Quinlan, EB, Rasser, PE, Ratnakar, V, Reppermund, S, Steen, VM, Tooney, PA, Torres, FR, Veltman, DJ, Voyvodic, JT, Whelan, R, White, T, Yamamori, H, Adams, HHH, Bis, JC, Debette, S, Decarli, C, Fornage, M, Gudnason, V, Hofer, E, Ikram, MA, Launer, L, Longstreth, WT, Lopez, OL, Mazoyer, B, Mosley, TH, Roshchupkin, GV, Satizabal, CL, Schmidt, R, Seshadri, S, Yang, Q, Alvim, MKM, Ames, D, Anderson, TJ, Andreassen, OA, Arias-Vasquez, A, Bastin, ME, Baune, BT, Beckham, JC, Blangero, J, Boomsma, DI, Brodaty, H, Brunner, HG, Buckner, RL, Buitelaar, JK, Bustillo, JR, Cahn, W, Cairns, MJ, Calhoun, V, Carr, VJ, Caseras, X, Caspers, S, Cavalleri, GL, Cendes, F, Corvin, A, Crespo-Facorro, B, Dalrymple-Alford, JC, Dannlowski, U, de Geus, EJC, Deary, IJ, Delanty, N, Depondt, C, Desrivieres, S, Donohoe, G, Espeseth, T, Fernandez, G, Fisher, SE, Flor, H, Forstner, AJ, Francks, C, Franke, B, Glahn, DC, Gollub, RL, Grabe, HJ, Gruber, O, Haberg, AK, Hariri, AR, Hartman, CA, Hashimoto, R, Heinz, A, Henskens, FA, Hillegers, MHJ, Hoekstra, PJ, Holmes, AJ, Hong, LE, Hopkins, WD, Pol, HEH, Jernigan, TL, Jonsson, EG, Kahn, RS, Kennedy, MA, Kircher, TTJ, Kochunov, P, Kwok, JBJ, Le Hellard, S, Loughland, CM, Martin, NG, Martinot, J-L, McDonald, C, McMahon, KL, Meyer-Lindenberg, A, Michie, PT, Morey, RA, Mowry, B, Nyberg, L, Oosterlaan, J, Ophoff, RA, Pantelis, C, Paus, T, Pausova, Z, Penninx, BWJH, Polderman, TJC, Posthuma, D, Rietschel, M, Roffman, JL, Rowland, LM, Sachdev, PS, Samann, PG, Schall, U, Schumann, G, Scott, RJ, Sim, K, Sisodiya, SM, Smoller, JW, Sommer, IE, St Pourcain, B, Stein, DJ, Toga, AW, Trollor, JN, Van der Wee, NJA, van't Ent, D, Volzke, H, Walter, H, Weber, B, Weinberger, DR, Wright, MJ, Zhou, J, Stein, JL, Thompson, PM, and Medland, SE
Abstract: The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
Published: 2020

41. Single-subject grey matter network trajectories over the disease course of autosomal dominant Alzheimer's disease

Author: Vermunt, L, Dicks, E, Wang, G, Dincer, A, Flores, S, Keefe, SJ, Berman, SB, Cash, DM, Chhatwal, JP, Cruchaga, C, Fox, NC, Ghetti, B, Graff-Radford, NR, Hassenstab, J, Karch, CM, Laske, C, Levin, J, Masters, CL, McDade, E, Mori, H, Morris, JC, Noble, JM, Perrin, RJ, Schofield, PR, Xiong, C, Scheltens, P, Visser, PJ, Bateman, RJ, Benzinger, TLS, Tijms, BM, Gordon, BA, Vermunt, L, Dicks, E, Wang, G, Dincer, A, Flores, S, Keefe, SJ, Berman, SB, Cash, DM, Chhatwal, JP, Cruchaga, C, Fox, NC, Ghetti, B, Graff-Radford, NR, Hassenstab, J, Karch, CM, Laske, C, Levin, J, Masters, CL, McDade, E, Mori, H, Morris, JC, Noble, JM, Perrin, RJ, Schofield, PR, Xiong, C, Scheltens, P, Visser, PJ, Bateman, RJ, Benzinger, TLS, Tijms, BM, and Gordon, BA
Abstract: Structural grey matter covariance networks provide an individual quantification of morphological patterns in the brain. The network integrity is disrupted in sporadic Alzheimer's disease, and network properties show associations with the level of amyloid pathology and cognitive decline. Therefore, these network properties might be disease progression markers. However, it remains unclear when and how grey matter network integrity changes with disease progression. We investigated these questions in autosomal dominant Alzheimer's disease mutation carriers, whose conserved age at dementia onset allows individual staging based upon their estimated years to symptom onset. From the Dominantly Inherited Alzheimer Network observational cohort, we selected T1-weighted MRI scans from 269 mutation carriers and 170 non-carriers (mean age 38 ± 15 years, mean estimated years to symptom onset -9 ± 11), of whom 237 had longitudinal scans with a mean follow-up of 3.0 years. Single-subject grey matter networks were extracted, and we calculated for each individual the network properties which describe the network topology, including the size, clustering, path length and small worldness. We determined at which time point mutation carriers and non-carriers diverged for global and regional grey matter network metrics, both cross-sectionally and for rate of change over time. Based on cross-sectional data, the earliest difference was observed in normalized path length, which was decreased for mutation carriers in the precuneus area at 13 years and on a global level 12 years before estimated symptom onset. Based on longitudinal data, we found the earliest difference between groups on a global level 6 years before symptom onset, with a greater rate of decline of network size for mutation carriers. We further compared grey matter network small worldness with established biomarkers for Alzheimer disease (i.e. amyloid accumulation, cortical thickness, brain metabolism and cognitive function). We
Published: 2020

42. Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease-informed machine-learning

Author: Franzmeier, N, Koutsouleris, N, Benzinger, T, Goate, A, Karch, CM, Fagan, AM, McDade, E, Duering, M, Dichgans, M, Levin, J, Gordon, BA, Lim, YY, Masters, CL, Rossor, M, Fox, NC, O'Connor, A, Chhatwal, J, Salloway, S, Danek, A, Hassenstab, J, Schofield, PR, Morris, JC, Bateman, RJ, Ewers, M, Franzmeier, N, Koutsouleris, N, Benzinger, T, Goate, A, Karch, CM, Fagan, AM, McDade, E, Duering, M, Dichgans, M, Levin, J, Gordon, BA, Lim, YY, Masters, CL, Rossor, M, Fox, NC, O'Connor, A, Chhatwal, J, Salloway, S, Danek, A, Hassenstab, J, Schofield, PR, Morris, JC, Bateman, RJ, and Ewers, M
Abstract: INTRODUCTION: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge. METHODS: We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid-PET and fluorodeoxyglucose positron-emission tomography (FDG-PET) to predict rates of cognitive decline. Prediction models were trained in autosomal-dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross-validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model-based risk enrichment was estimated. RESULTS: A model combining all biomarker modalities and established in ADAD predicted the 4-year rate of decline in global cognition (R2 = 24%) and memory (R2 = 25%) in sporadic AD. Model-based risk-enrichment reduced the sample size required for detecting simulated intervention effects by 50%-75%. DISCUSSION: Our independently validated machine-learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD.
Published: 2020

43. Genome-wide association study of 23,500 individuals identifies 7 loci associated with brain ventricular volume

Author: Vojinovic, D, Adams, HH, Jian, X, Yang, Q, Smith, AV, Bis, JC, Teumer, A, Scholz, M, Armstrong, NJ, Hofer, E, Saba, Y, Luciano, M, Bernard, M, Trompet, S, Yang, J, Gillespie, NA, van der Lee, SJ, Neumann, A, Ahmad, S, Andreassen, OA, Ames, D, Amin, N, Arfanakis, K, Bastin, ME, Becker, DM, Beiser, AS, Beyer, F, Brodaty, H, Bryan, RN, Bülow, R, Dale, AM, De Jager, PL, Deary, IJ, DeCarli, C, Fleischman, DA, Gottesman, RF, van der Grond, J, Gudnason, V, Harris, TB, Homuth, G, Knopman, DS, Kwok, JB, Lewis, CE, Li, S, Loeffler, M, Lopez, OL, Maillard, P, El Marroun, H, Mather, KA, Mosley, TH, Muetzel, RL, Nauck, M, Nyquist, PA, Panizzon, MS, Pausova, Z, Psaty, BM, Rice, K, Rotter, JI, Royle, N, Satizabal, CL, Schmidt, R, Schofield, PR, Schreiner, PJ, Sidney, S, Stott, DJ, Thalamuthu, A, Uitterlinden, AG, and Valdés Hernández, MC
Abstract: © 2018, The Author(s). The volume of the lateral ventricles (LV) increases with age and their abnormal enlargement is a key feature of several neurological and psychiatric diseases. Although lateral ventricular volume is heritable, a comprehensive investigation of its genetic determinants is lacking. In this meta-analysis of genome-wide association studies of 23,533 healthy middle-aged to elderly individuals from 26 population-based cohorts, we identify 7 genetic loci associated with LV volume. These loci map to chromosomes 3q28, 7p22.3, 10p12.31, 11q23.1, 12q23.3, 16q24.2, and 22q13.1 and implicate pathways related to tau pathology, S1P signaling, and cytoskeleton organization. We also report a significant genetic overlap between the thalamus and LV volumes (?genetic = -0.59, p-value = 3.14 × 10-6), suggesting that these brain structures may share a common biology. These genetic associations of LV volume provide insights into brain morphology.
Published: 2018

44. The Association Between Familial Risk and Brain Abnormalities Is Disease Specific: An ENIGMA-Relatives Study of Schizophrenia and Bipolar Disorder

Author: de Zwarte, SMC, Brouwer, RM, Agartz, I, Alda, M, Aleman, A, Alpert, KI, Bearden, CE, Bertolino, A, Bois, C, Bonvino, A, Bramon, E, Buimer, EEL, Cahn, W, Cannon, DM, Cannon, TD, Caseras, X, Castro-Fornieles, J, Chen, Q, Chung, Y, De la Serna, E, Di Giorgio, A, Doucet, GE, Eker, MC, Erk, S, Fears, SC, Foley, SF, Frangou, S, Frankland, A, Fullerton, JM, Glahn, DC, Goghari, VM, Goldman, AL, Gonul, AS, Gruber, O, de Haan, L, Hajek, T, Hawkins, EL, Heinz, A, Hillegers, MHJ, Hulshoff Pol, HE, Hultman, CM, Ingvar, M, Johansson, V, Jönsson, EG, Kane, F, Kempton, MJ, Koenis, MMG, Kopecek, M, Krabbendam, L, Krämer, B, Lawrie, SM, Lenroot, RK, Marcelis, M, Marsman, JBC, Mattay, VS, McDonald, C, Meyer-Lindenberg, A, Michielse, S, Mitchell, PB, Moreno, D, Murray, RM, Mwangi, B, Najt, P, Neilson, E, Newport, J, van Os, J, Overs, B, Ozerdem, A, Picchioni, MM, Richter, A, Roberts, G, Aydogan, AS, Schofield, PR, Simsek, F, Soares, JC, Sugranyes, G, Toulopoulou, T, Tronchin, G, Walter, H, Wang, L, Weinberger, DR, Whalley, HC, Yalin, N, Andreassen, OA, Ching, CRK, van Erp, TGM, Turner, JA, Jahanshad, N, Thompson, PM, Kahn, RS, van Haren, NEM, de Zwarte, SMC, Brouwer, RM, Agartz, I, Alda, M, Aleman, A, Alpert, KI, Bearden, CE, Bertolino, A, Bois, C, Bonvino, A, Bramon, E, Buimer, EEL, Cahn, W, Cannon, DM, Cannon, TD, Caseras, X, Castro-Fornieles, J, Chen, Q, Chung, Y, De la Serna, E, Di Giorgio, A, Doucet, GE, Eker, MC, Erk, S, Fears, SC, Foley, SF, Frangou, S, Frankland, A, Fullerton, JM, Glahn, DC, Goghari, VM, Goldman, AL, Gonul, AS, Gruber, O, de Haan, L, Hajek, T, Hawkins, EL, Heinz, A, Hillegers, MHJ, Hulshoff Pol, HE, Hultman, CM, Ingvar, M, Johansson, V, Jönsson, EG, Kane, F, Kempton, MJ, Koenis, MMG, Kopecek, M, Krabbendam, L, Krämer, B, Lawrie, SM, Lenroot, RK, Marcelis, M, Marsman, JBC, Mattay, VS, McDonald, C, Meyer-Lindenberg, A, Michielse, S, Mitchell, PB, Moreno, D, Murray, RM, Mwangi, B, Najt, P, Neilson, E, Newport, J, van Os, J, Overs, B, Ozerdem, A, Picchioni, MM, Richter, A, Roberts, G, Aydogan, AS, Schofield, PR, Simsek, F, Soares, JC, Sugranyes, G, Toulopoulou, T, Tronchin, G, Walter, H, Wang, L, Weinberger, DR, Whalley, HC, Yalin, N, Andreassen, OA, Ching, CRK, van Erp, TGM, Turner, JA, Jahanshad, N, Thompson, PM, Kahn, RS, and van Haren, NEM
Abstract: Background: Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects. Methods: We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects. Results: FDRs-BD had significantly larger ICV (d = +0.16, q <.05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = −0.12, q <.05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < −0.09, q <.05 corrected); and third ventricle was larger (d = +0.15, q <.05 corrected). The findings were not explained by psychopathology in the relatives or control subjects. Conclusions: Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct.
Published: 2019

45. A Neuroethics Framework for the Australian Brain Initiative

Author: Kennett, J, Carter, A, Bourne, JA, Hall, W, Levy, N, Mattingley, JB, Lawrence, AJ, Forlini, C, Malcolm, L, Vincent, N, Richards, LJ, Egan, GF, Breakspear, M, Cornish, K, Halliday, G, Poole-Warren, L, Sriram, S, Soulis, T, Fitzgibbon, B, Kiral-Kornek, I, Badcock, DR, Balleine, B, Bekkers, JM, Berk, M, Bradley, A, Brichta, A, Carter, O, Castles, A, Clements, J, Cornish, J, de Zubicaray, G, Enticott, PG, Fornito, A, Griffiths, L, Gullifer, J, Hannan, AJ, Harrer, S, Harvey, A, Hickie, IB, Jazwinska, L, Kiernan, M, Kilpatrick, T, Leventer, R, Licinio, J, Lovell, N, Mackellar, G, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Rossell, S, Sah, P, Sarnyai, Z, Schofield, PR, Shum, DHK, Silk, T, Slee, M, Stuart, GJ, Tapson, J, van Schaik, A, Vissel, B, Waters, A, Apthorp, D, Cohen-Woods, S, Conn, SJ, Korgaonkar, M, Mason, A, Azghadi, MR, Shimoni, O, Smith, A, Thompson, MB, Kennett, J, Carter, A, Bourne, JA, Hall, W, Levy, N, Mattingley, JB, Lawrence, AJ, Forlini, C, Malcolm, L, Vincent, N, Richards, LJ, Egan, GF, Breakspear, M, Cornish, K, Halliday, G, Poole-Warren, L, Sriram, S, Soulis, T, Fitzgibbon, B, Kiral-Kornek, I, Badcock, DR, Balleine, B, Bekkers, JM, Berk, M, Bradley, A, Brichta, A, Carter, O, Castles, A, Clements, J, Cornish, J, de Zubicaray, G, Enticott, PG, Fornito, A, Griffiths, L, Gullifer, J, Hannan, AJ, Harrer, S, Harvey, A, Hickie, IB, Jazwinska, L, Kiernan, M, Kilpatrick, T, Leventer, R, Licinio, J, Lovell, N, Mackellar, G, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Rossell, S, Sah, P, Sarnyai, Z, Schofield, PR, Shum, DHK, Silk, T, Slee, M, Stuart, GJ, Tapson, J, van Schaik, A, Vissel, B, Waters, A, Apthorp, D, Cohen-Woods, S, Conn, SJ, Korgaonkar, M, Mason, A, Azghadi, MR, Shimoni, O, Smith, A, and Thompson, MB
Abstract: Neuroethics is central to the Australian Brain Initiative's aim to sustain a thriving and responsible neurotechnology industry. Diverse and inclusive community and stakeholder engagement and a trans-disciplinary approach to neuroethics will be key to the success of the Australian Brain Initiative.
Published: 2019

46. Correction: Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals (Neuropsychopharmacology, (2019), 44, 13, (2285-2293), 10.1038/s41386-019-0485-6)

Author: Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, Houenou, J, Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, and Houenou, J
Abstract: This Article was originally published under NPG's License to Publish, but has now been made available under a [CC BY 4.0] license. The PDF and HTML versions of the Article have been modified accordingly.
Published: 2019

47. Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals

Author: Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, Houenou, J, Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, and Houenou, J
Abstract: Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R2 = 0.041, Pcorr < 0.001) and cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr < 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.
Published: 2019

48. Role of epigenetic age and stress in developing bipolar disorder at high familial risk

Author: Hesam-Shariati, S, Overs, BJ, Green, MJ, Roberts, G, Leung, V, Stuart, A, Schofield, PR, Mitchell, PB, Fullerton, JM, Hesam-Shariati, S, Overs, BJ, Green, MJ, Roberts, G, Leung, V, Stuart, A, Schofield, PR, Mitchell, PB, and Fullerton, JM
Published: 2019

49. THE RELATIONSHIP BETWEEN FUNCTIONAL DOPAMINE D2 RECEPTOR HAPLOTYPES AND COGNITIVE OUTCOMES, AS MEDIATED BY REGIONAL BRAIN STRUCTURE: A COMPARISON OF CONTROL, AT-RISK, AND BIPOLAR DISORDER SUBJECTS

Author: Overs, BJ, Lenroot, RK, Roberts, G, Green, MJ, Hadzi-Pavlovic, D, Frankland, A, Levy, F, Toma, C, Schofield, PR, Mitchell, PB, Fullerton, J, Overs, BJ, Lenroot, RK, Roberts, G, Green, MJ, Hadzi-Pavlovic, D, Frankland, A, Levy, F, Toma, C, Schofield, PR, Mitchell, PB, and Fullerton, J
Published: 2019

50. The role of rare variants in bipolar disorder

Author: Toma, C, Shaw, AD, Allcock, RJN, Heath, A, Pierce, KD, Cooper, A, Mitchell, PB, Schofield, PR, Fullerton, JM, Toma, C, Shaw, AD, Allcock, RJN, Heath, A, Pierce, KD, Cooper, A, Mitchell, PB, Schofield, PR, and Fullerton, JM
Published: 2019

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