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Identifying neural correlates of memory and language disturbances in herpes simplex encephalitis: a voxel-based morphometry (VBM) study.
LIFE Adult

Abstract (Expand)

Herpes simplex encephalitis (HSE) is a severe neurological disease that often leads to persistent cognitive deficits in survivors. Memory and naming impairments have been reported most, although direct … association between memory and naming performance and disease-related atrophy has not yet been demonstrated in vivo for a larger sample of patients. In the present work, a voxel-based morphometry (VBM) analysis was conducted on 3T magnetic resonance imaging (MRI) of 13 HSE survivors. The gray matter density values were correlated with scores indicating verbal memory decline, as well as errors/omissions in picture naming; both were obtained through neuropsychological assessment. Analysis of individual lesion patterns revealed a considerable inter-individual variability, mainly with atrophy in the basal forebrain, adjacent frontal cortex, medial and lateral temporal cortex, insula and thalamus. The neuropsychological data analysis revealed correlation between verbal memory decline and atrophy especially in the left hippocampal region, whereas naming problems were associated with gray matter loss especially in the lateral temporal lobe, the thalamus and the left insula. These results confirm, for the first time, the assumptions of earlier studies about the considerable variability of individual lesion patterns in HSE in a whole-brain approach in vivo, and thus the anatomical validity of VBM.

Authors: S. Frisch, F. Thiel, A. Marschhauser, A. Villringer, A. Horstmann, M. L. Schroeter

Date Published: 10th Dec 2014

Publication Type: Not specified

Human Diseases: viral encephalitis

Refined histopathological predictors of BRCA1 and BRCA2 mutation status: a large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

INTRODUCTION The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological …l features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. METHODS Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the likelihood of mutation status by histopathological markers were derived using a Mantel-Haenszel approach. RESULTS ER-positive phenotype negatively predicted BRCA1 mutation status, irrespective of grade (LRs from 0.08 to 0.90). ER-negative grade 3 histopathology was more predictive of positive BRCA1 mutation status in women 50 years or older (LR = 4.13 (3.70 to 4.62)) versus younger than 50 years (LR = 3.16 (2.96 to 3.37)). For BRCA2, ER-positive grade 3 phenotype modestly predicted positive mutation status irrespective of age (LR = 1.7-fold), whereas ER-negative grade 3 features modestly predicted positive mutation status at 50 years or older (LR = 1.54 (1.27 to 1.88)). Triple-negative tumor status was highly predictive of BRCA1 mutation status for women younger than 50 years (LR = 3.73 (3.43 to 4.05)) and 50 years or older (LR = 4.41 (3.86 to 5.04)), and modestly predictive of positive BRCA2 mutation status in women 50 years or older (LR = 1.79 (1.42 to 2.24)). CONCLUSIONS These results refine likelihood-ratio estimates for predicting BRCA1 and BRCA2 mutation status by using commonly measured histopathological features. Age at diagnosis is an important variable for most analyses, and grade is more informative than ER status for BRCA2 mutation carrier prediction. The estimates will improve BRCA1 and BRCA2 variant classification and inform patient mutation testing and clinical management.

Authors: Amanda B. Spurdle, Fergus J. Couch, Michael T. Parsons, Lesley McGuffog, Daniel Barrowdale, Manjeet K. Bolla, Qin Wang, Sue Healey, Rita Schmutzler, Barbara Wappenschmidt, Kerstin Rhiem, Eric Hahnen, Christoph Engel, Alfons Meindl, Nina Ditsch, Norbert Arnold, Hansjoerg Plendl, Dieter Niederacher, Christian Sutter, Shan Wang-Gohrke, Doris Steinemann, Sabine Preisler-Adams, Karin Kast, Raymonda Varon-Mateeva, Steve Ellis, Debra Frost, Radka Platte, Jo Perkins, D. Gareth Evans, Louise Izatt, Ros Eeles, Julian Adlard, Rosemarie Davidson, Trevor Cole, Giulietta Scuvera, Siranoush Manoukian, Bernardo Bonanni, Frederique Mariette, Stefano Fortuzzi, Alessandra Viel, Barbara Pasini, Laura Papi, Liliana Varesco, Rosemary Balleine, Katherine L. Nathanson, Susan M. Domchek, Kenneth Offitt, Anna Jakubowska, Noralane Lindor, Mads Thomassen, Uffe Birk Jensen, Johanna Rantala, Åke Borg, Irene L. Andrulis, Alexander Miron, Thomas v. O. Hansen, Trinidad Caldes, Susan L. Neuhausen, Amanda E. Toland, Heli Nevanlinna, Marco Montagna, Judy Garber, Andrew K. Godwin, Ana Osorio, Rachel E. Factor, Mary B. Terry, Timothy R. Rebbeck, Beth Y. Karlan, Melissa Southey, Muhammad Usman Rashid, Nadine Tung, Paul D. P. Pharoah, Fiona M. Blows, Alison M. Dunning, Elena Provenzano, Per Hall, Kamila Czene, Marjanka K. Schmidt, Annegien Broeks, Sten Cornelissen, Senno Verhoef, Peter A. Fasching, Matthias W. Beckmann, Arif B. Ekici, Dennis J. Slamon, Stig E. Bojesen, Børge G. Nordestgaard, Sune F. Nielsen, Henrik Flyger, Jenny Chang-Claude, Dieter Flesch-Janys, Anja Rudolph, Petra Seibold, Kristiina Aittomäki, Taru A. Muranen, Päivi Heikkilä, Carl Blomqvist, Jonine Figueroa, Stephen J. Chanock, Louise Brinton, Jolanta Lissowska, Janet E. Olson, Vernon S. Pankratz, Esther M. John, Alice S. Whittemore, Dee W. West, Ute Hamann, Diana Torres, Hans Ulrich Ulmer, Thomas Rüdiger, Peter Devilee, Robert A. E. M. Tollenaar, Caroline Seynaeve, Christi J. van Asperen, Diana M. Eccles, William J. Tapper, Lorraine Durcan, Louise Jones, Julian Peto, Isabel Dos-Santos-Silva, Olivia Fletcher, Nichola Johnson, Miriam Dwek, Ruth Swann, Anita L. Bane, Gord Glendon, Anna M. Mulligan, Graham G. Giles, Roger L. Milne, Laura Baglietto, Catriona McLean, Jane Carpenter, Christine Clarke, Rodney Scott, Hiltrud Brauch, Thomas Brüning, Yon-Dschun Ko, Angela Cox, Simon S. Cross, Malcolm W. R. Reed, Jan Lubinski, Katarzyna Jaworska-Bieniek, Katarzyna Durda, Jacek Gronwald, Thilo Dörk, Natalia Bogdanova, Tjoung-Won Park-Simon, Peter Hillemanns, Christopher A. Haiman, Brian E. Henderson, Fredrick Schumacher, Loic Le Marchand, Barbara Burwinkel, Frederik Marme, Harald Surovy, Rongxi Yang, Hoda Anton-Culver, Argyrios Ziogas, Maartje J. Hooning, J. Margriet Collée, John W. M. Martens, Madeleine M. A. Tilanus-Linthorst, Hermann Brenner, Aida Karina Dieffenbach, Volke Arndt, Christa Stegmaier, Robert Winqvist, Katri Pylkäs, Arja Jukkola-Vuorinen, Mervi Grip, Annika Lindblom, Sara Margolin, Vijai Joseph, Mark Robson, Rohini Rau-Murthy, Anna González-Neira, José Ignacio Arias, Pilar Zamora, Javier Benítez, Arto Mannermaa, Vesa Kataja, Veli-Matti Kosma, Jaana M. Hartikainen, Paolo Peterlongo, Daniela Zaffaroni, Monica Barile, Fabio Capra, Paolo Radice, Soo H. Teo, Douglas F. Easton, Antonis C. Antoniou, Georgia Chenevix-Trench, David E. Goldgar

Date Published: 1st Dec 2014

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Associations of common breast cancer susceptibility alleles with risk of breast cancer subtypes in BRCA1 and BRCA2 mutation carriers
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

INTRODUCTION More than 70 common alleles are known to be involved in breast cancer (BC) susceptibility, and several exhibit significant heterogeneity in their associations with different BC subtypes. …. Although there are differences in the association patterns between BRCA1 and BRCA2 mutation carriers and the general population for several loci, no study has comprehensively evaluated the associations of all known BC susceptibility alleles with risk of BC subtypes in BRCA1 and BRCA2 carriers. METHODS We used data from 15,252 BRCA1 and 8,211 BRCA2 carriers to analyze the associations between approximately 200,000 genetic variants on the iCOGS array and risk of BC subtypes defined by estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and triple-negative- (TN) status; morphologic subtypes; histological grade; and nodal involvement. RESULTS The estimated BC hazard ratios (HRs) for the 74 known BC alleles in BRCA1 carriers exhibited moderate correlations with the corresponding odds ratios from the general population. However, their associations with ER-positive BC in BRCA1 carriers were more consistent with the ER-positive associations in the general population (intraclass correlation (ICC) = 0.61, 95% confidence interval (CI): 0.45 to 0.74), and the same was true when considering ER-negative associations in both groups (ICC = 0.59, 95% CI: 0.42 to 0.72). Similarly, there was strong correlation between the ER-positive associations for BRCA1 and BRCA2 carriers (ICC = 0.67, 95% CI: 0.52 to 0.78), whereas ER-positive associations in any one of the groups were generally inconsistent with ER-negative associations in any of the others. After stratifying by ER status in mutation carriers, additional significant associations were observed. Several previously unreported variants exhibited associations at P \textless10(-6) in the analyses by PR status, HER2 status, TN phenotype, morphologic subtypes, histological grade and nodal involvement. CONCLUSIONS Differences in associations of common BC susceptibility alleles between BRCA1 and BRCA2 carriers and the general population are explained to a large extent by differences in the prevalence of ER-positive and ER-negative tumors. Estimates of the risks associated with these variants based on population-based studies are likely to be applicable to mutation carriers after taking ER status into account, which has implications for risk prediction.

Authors: Karoline B. Kuchenbaecker, Susan L. Neuhausen, Mark Robson, Daniel Barrowdale, Lesley McGuffog, Anna Marie Mulligan, Irene L. Andrulis, Amanda B. Spurdle, Marjanka K. Schmidt, Rita K. Schmutzler, Christoph Engel, Barbara Wappenschmidt, Heli Nevanlinna, Mads Thomassen, Melissa Southey, Paolo Radice, Susan J. Ramus, Susan M. Domchek, Katherine L. Nathanson, Andrew Lee, Sue Healey, Robert L. Nussbaum, Timothy R. Rebbeck, Banu K. Arun, Paul James, Beth Y. Karlan, Jenny Lester, Ilana Cass, Mary Beth Terry, Mary B. Daly, David E. Goldgar, Saundra S. Buys, Ramunas Janavicius, Laima Tihomirova, Nadine Tung, Cecilia M. Dorfling, Elizabeth J. van Rensburg, Linda Steele, Thomas v O Hansen, Bent Ejlertsen, Anne-Marie Gerdes, Finn C. Nielsen, Joe Dennis, Julie Cunningham, Steven Hart, Susan Slager, Ana Osorio, Javier Benitez, Mercedes Duran, Jeffrey N. Weitzel, Isaac Tafur, Mary Hander, Paolo Peterlongo, Siranoush Manoukian, Bernard Peissel, Gaia Roversi, Giulietta Scuvera, Bernardo Bonanni, Paolo Mariani, Sara Volorio, Riccardo Dolcetti, Liliana Varesco, Laura Papi, Maria Grazia Tibiletti, Giuseppe Giannini, Florentia Fostira, Irene Konstantopoulou, Judy Garber, Ute Hamann, Alan Donaldson, Carole Brewer, Claire Foo, D. Gareth Evans, Debra Frost, Diana Eccles, Fiona Douglas, Angela Brady, Jackie Cook, Marc Tischkowitz, Julian Adlard, Julian Barwell, Kai-Ren Ong, Lisa Walker, Louise Izatt, Lucy E. Side, M. John Kennedy, Mark T. Rogers, Mary E. Porteous, Patrick J. Morrison, Radka Platte, Ros Eeles, Rosemarie Davidson, Shirley Hodgson, Steve Ellis, Andrew K. Godwin, Kerstin Rhiem, Alfons Meindl, Nina Ditsch, Norbert Arnold, Hansjoerg Plendl, Dieter Niederacher, Christian Sutter, Doris Steinemann, Nadja Bogdanova-Markov, Karin Kast, Raymonda Varon-Mateeva, Shan Wang-Gohrke, Andrea Gehrig, Birgid Markiefka, Bruno Buecher, Cédrick Lefol, Dominique Stoppa-Lyonnet, Etienne Rouleau, Fabienne Prieur, Francesca Damiola, Laure Barjhoux, Laurence Faivre, Michel Longy, Nicolas Sevenet, Olga M. Sinilnikova, Sylvie Mazoyer, Valérie Bonadona, Virginie Caux-Moncoutier, Claudine Isaacs, Tom van Maerken, Kathleen Claes, Marion Piedmonte, Lesley Andrews, John Hays, Gustavo C. Rodriguez, Trinidad Caldes, Miguel de La Hoya, Sofia Khan, Frans B. L. Hogervorst, Cora M. Aalfs, J. L. de Lange, Hanne E. J. Meijers-Heijboer, Annemarie H. van der Hout, Juul T. Wijnen, K. E. P. van Roozendaal, Arjen R. Mensenkamp, Ans M. W. van den Ouweland, Carolien H. M. van Deurzen, Rob B. van der Luijt, Edith Olah, Orland Diez, Conxi Lazaro, Ignacio Blanco, Alex Teulé, Mireia Menendez, Anna Jakubowska, Jan Lubinski, Cezary Cybulski, Jacek Gronwald, Katarzyna Jaworska-Bieniek, Katarzyna Durda, Adalgeir Arason, Christine Maugard, Penny Soucy, Marco Montagna, Simona Agata, Manuel R. Teixeira, Curtis Olswold, Noralane Lindor, Vernon S. Pankratz, Emily Hallberg, Xianshu Wang, Csilla I. Szabo, Joseph Vijai, Lauren Jacobs, Marina Corines, Anne Lincoln, Andreas Berger, Anneliese Fink-Retter, Christian F. Singer, Christine Rappaport, Daphne Gschwantler Kaulich, Georg Pfeiler, Muy-Kheng Tea, Catherine M. Phelan, Phuong L. Mai, Mark H. Greene, Gad Rennert, Evgeny N. Imyanitov, Gord Glendon, Amanda Ewart Toland, Anders Bojesen, Inge Sokilde Pedersen, Uffe Birk Jensen, Maria A. Caligo, Eitan Friedman, Raanan Berger, Yael Laitman, Johanna Rantala, Brita Arver, Niklas Loman, Ake Borg, Hans Ehrencrona, Olufunmilayo I. Olopade, Jacques Simard, Douglas F. Easton, Georgia Chenevix-Trench, Kenneth Offit, Fergus J. Couch, Antonis C. Antoniou

Date Published: 1st Dec 2014

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Sepsis survivors monitoring and coordination in outpatient health care (SMOOTH): study protocol for a randomized controlled trial
SepNet - German Competence Network Sepsis

Abstract (Expand)

BACKGROUND Sepsis sequelae include critical illness polyneuropathy, myopathy, wasting, neurocognitive deficits, post-traumatic stress disorder, depression and chronic pain. Little is known howlong-term …m sequelae following hospital discharge are treated. The aim of our study is to determine the effect of a primary care-based, long-term program on health-related quality of life in sepsis survivors. METHODS/DESIGN In a two-armed randomized multicenter interventional study, patients after sepsis (n = 290) will be assessed at 6, 12 and 24 months. Patients are eligible if severe sepsis or septic shock (ICD-10), at least two criteria of systemic inflammatory response syndrome (SIRS), at least one organ dysfunction and sufficient cognitive capacity are present. The intervention comprises 1) discharge management, 2) training of general practitioners and patients in evidence-based care for sepsis sequelae and 3) telephone monitoring of patients. At six months, we expect an improved primary outcome (health-related quality of life/SF-36) and improved secondary outcomes such as costs, mortality, clinical-, psycho-social- and process-of-care measures in the intervention group compared to the control group. DISCUSSION This study evaluates a primary care-based, long-term program for patients after severe sepsis. Study results may add evidence for improved sepsis care management. General practitioners may contribute efficiently to sepsis aftercare. TRIAL REGISTRATION U1111-1119-6345. DRKS00000741, CCT-NAPN-20875 (25 February 2011).

Authors: Konrad Schmidt, Paul Thiel, Friederike Mueller, Katja Schmuecker, Susanne Worrack, Juliane Mehlhorn, Christoph Engel, Katja Brenk-Franz, Stephan Kausche, Ursula Jakobi, Anne Bindara-Klippel, Nico Schneider, Antje Freytag, Dimitry Davydow, Michel Wensing, Frank Martin Brunkhorst, Jochen Gensichen

Date Published: 1st Dec 2014

Publication Type: Journal article

Human Diseases: disease by infectious agent

Ycasd - a tool for capturing and scaling data from graphical representations
Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND\backslashr\backslashnMathematical modelling of biological processes often requires a large variety of different data sets for parameter estimation and validation. It is common practice that … clinical data are not available in raw formats but are provided as graphical representations. Hence, in order to include these data into environments used for model simulations and statistical analyses, it is necessary to extract them from their presentations in the literature. For this purpose, we developed the freely available open source tool ycasd. After establishing a coordinate system by simple axes definitions, it supports convenient retrieval of data points from arbitrary figures.\backslashr\backslashnRESULTS\backslashr\backslashnAfter describing the general functionality and providing an overview of the programme interface, we demonstrate on an example how to use ycasd. A major advantage of ycasd is that it does not require a certain input file format to open and process figures. All options of ycasd are accessible through a single window which eases handling and speeds up data extraction. For subsequent processing of extracted data points, results can be formatted as a Matlab or an R matrix. We extensively compare the functionality and other features of ycasd with other publically available tools. Finally, we provide a short summary of our experiences with ycasd in the context of modelling.\backslashr\backslashnCONCLUSIONS\backslashr\backslashnWe conclude that our tool is suitable for convenient and accurate data retrievals from graphical representations such as papers. Comparison of tools reveals that ycasd is a good compromise between easy and quick capturing of scientific data from publications and complexity. Our tool is routinely applied in the context of biological modelling, where numerous time series data are required to develop models. The software can also be useful for other kinds of analyses for which published data are required but are not available in raw formats such as systematic reviews and meta-analyses. BACKGROUND Mathematical modelling of biological processes often requires a large variety of different data sets for parameter estimation and validation. It is common practice that clinical data are not available in raw formats but are provided as graphical representations. Hence, in order to include these data into environments used for model simulations and statistical analyses, it is necessary to extract them from their presentations in the literature. For this purpose, we developed the freely available open source tool ycasd. After establishing a coordinate system by simple axes definitions, it supports convenient retrieval of data points from arbitrary figures. RESULTS After describing the general functionality and providing an overview of the programme interface, we demonstrate on an example how to use ycasd. A major advantage of ycasd is that it does not require a certain input file format to open and process figures. All options of ycasd are accessible through a single window which eases handling and speeds up data extraction. For subsequent processing of extracted data points, results can be formatted as a Matlab or an R matrix. We extensively compare the functionality and other features of ycasd with other publically available tools. Finally, we provide a short summary of our experiences with ycasd in the context of modelling. CONCLUSIONS We conclude that our tool is suitable for convenient and accurate data retrievals from graphical representations such as papers. Comparison of tools reveals that ycasd is a good compromise between easy and quick capturing of scientific data from publications and complexity. Our tool is routinely applied in the context of biological modelling, where numerous time series data are required to develop models. The software can also be useful for other kinds of analyses for which published data are required but are not available in raw formats such as systematic reviews and meta-analyses. BACKGROUND Mathematical modelling of biological processes often requires a large variety of different data sets for parameter estimation and validation. It is common practice that clinical data are not available in raw formats but are provided as graphical representations. Hence, in order to include these data into environments used for model simulations and statistical analyses, it is necessary to extract them from their presentations in the literature. For this purpose, we developed the freely available open source tool ycasd. After establishing a coordinate system by simple axes definitions, it supports convenient retrieval of data points from arbitrary figures. RESULTS After describing the general functionality and providing an overview of the programme interface, we demonstrate on an example how to use ycasd. A major advantage of ycasd is that it does not require a certain input file format to open and process figures. All options of ycasd are accessible through a single window which eases handling and speeds up data extraction. For subsequent processing of extracted data points, results can be formatted as a Matlab or an R matrix. We extensively compare the functionality and other features of ycasd with other publically available tools. Finally, we provide a short summary of our experiences with ycasd in the context of modelling. CONCLUSIONS We conclude that our tool is suitable for convenient and accurate data retrievals from graphical representations such as papers. Comparison of tools reveals that ycasd is a good compromise between easy and quick capturing of scientific data from publications and complexity. Our tool is routinely applied in the context of biological modelling, where numerous time series data are required to develop models. The software can also be useful for other kinds of analyses for which published data are required but are not available in raw formats such as systematic reviews and meta-analyses. BACKGROUND Mathematical modelling of biological processes often requires a large variety of different data sets for parameter estimation and validation. It is common practice that clinical data are not available in raw formats but are provided as graphical representations. Hence, in order to include these data into environments used for model simulations and statistical analyses, it is necessary to extract them from their presentations in the literature. For this purpose, we developed the freely available open source tool ycasd. After establishing a coordinate system by simple axes definitions, it supports convenient retrieval of data points from arbitrary figures. RESULTS After describing the general functionality and providing an overview of the programme interface, we demonstrate on an example how to use ycasd. A major advantage of ycasd is that it does not require a certain input file format to open and process figures. All options of ycasd are accessible through a single window which eases handling and speeds up data extraction. For subsequent processing of extracted data points, results can be formatted as a Matlab or an R matrix. We extensively compare the functionality and other features of ycasd with other publically available tools. Finally, we provide a short summary of our experiences with ycasd in the context of modelling. CONCLUSIONS We conclude that our tool is suitable for convenient and accurate data retrievals from graphical representations such as papers. Comparison of tools reveals that ycasd is a good compromise between easy and quick capturing of scientific data from publications and complexity. Our tool is routinely applied in the context of biological modelling, where numerous time series data are required to develop models. The software can also be useful for other kinds of analyses for which published data are required but are not available in raw formats such as systematic reviews and meta-analyses.

Authors: Arnd Gross, Sibylle Schirm, Markus Scholz

Date Published: 1st Dec 2014

Publication Type: Journal article

Impact of pre-imputation SNP-filtering on genotype imputation results
Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND Imputation of partially missing or unobserved genotypes is an indispensable tool for SNP data analyses. However, research and understanding of the impact of initial SNP-data quality control …l on imputation results is still limited. In this paper, we aim to evaluate the effect of different strategies of pre-imputation quality filtering on the performance of the widely used imputation algorithms MaCH and IMPUTE. RESULTS We considered three scenarios: imputation of partially missing genotypes with usage of an external reference panel, without usage of an external reference panel, as well as imputation of completely un-typed SNPs using an external reference panel. We first created various datasets applying different SNP quality filters and masking certain percentages of randomly selected high-quality SNPs. We imputed these SNPs and compared the results between the different filtering scenarios by using established and newly proposed measures of imputation quality. While the established measures assess certainty of imputation results, our newly proposed measures focus on the agreement with true genotypes. These measures showed that pre-imputation SNP-filtering might be detrimental regarding imputation quality. Moreover, the strongest drivers of imputation quality were in general the burden of missingness and the number of SNPs used for imputation. We also found that using a reference panel always improves imputation quality of partially missing genotypes. MaCH performed slightly better than IMPUTE2 in most of our scenarios. Again, these results were more pronounced when using our newly defined measures of imputation quality. CONCLUSION Even a moderate filtering has a detrimental effect on the imputation quality. Therefore little or no SNP filtering prior to imputation appears to be the best strategy for imputing small to moderately sized datasets. Our results also showed that for these datasets, MaCH performs slightly better than IMPUTE2 in most scenarios at the cost of increased computing time.

Authors: Nab Raj Roshyara, Holger Kirsten, Katrin Horn, Peter Ahnert, Markus Scholz

Date Published: 1st Dec 2014

Publication Type: Journal article

Risk of dementia in older adults with low versus high occupation-based motivational processes: differential impact of frequency and proximity of social network.
LIFE Adult

Abstract (Expand)

OBJECTIVES: This study investigates the impact of occupation-based motivational processes and social network variables on the incidence of dementia over 8 years. METHOD: Data were derived from the … Leipzig Longitudinal Study of the Aged (LEILA75+), a population-based longitudinal study of individuals aged 75 years and older (n=1692 at baseline). Motivational processes were estimated based on the main occupation using the Occupational Information Network database. RESULTS: In a Cox proportional hazard model, motivational processes were not associated with the risk of dementia (hazard ratio [HR]: 0.93, 95% confidence interval [CI]: 0.74-1.16). Individuals with a higher frequency of social contact at baseline had a significantly lower risk of dementia (HR: 0.96, 95% CI: 0.91-0.99), while proximity of social contacts was not linked to the risk of dementia (HR: 1.03, 95% CI: 0.98-1.08). In individuals with low indices of motivational processes, the frequency of social contacts was associated with a lower risk of dementia (HR: 0.94, 95% CI: 0.88-1.00). On the other hand, proximity of social contacts was linked to a higher risk of dementia in individuals with high indices of motivational processes (HR: 1.09, 95% CI: 1.01-1.19). DISCUSSION: Results indicate that the frequency and proximity of social contacts have a differential impact on the risk of dementia according to lower or higher indices of motivational processes, while the impact of motivational processes on risk of dementia could not be confirmed. Future studies should carefully disentangle different aspects of social interactions and their association with motivational processes.

Authors: S. Fankhauser, S. Forstmeier, A. Maercker, M. Luppa, T. Luck, S. G. Riedel-Heller

Date Published: 29th Nov 2014

Publication Type: Not specified

Human Diseases: dementia

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