Christine Van Broeckhoven

Prof. Dr. Christine Van Broeckhoven

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Academic Career Length

37Years (1990-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 March 2018 in Bioinformatics
Verified
Journal Article
Open access
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WCWouter De Coster
Wouter De Coster
SDSvenn D’hert
Svenn D’hert
DSDarrin T Schultz
Darrin T Schultz
MCMarc Cruts
Marc Cruts
CBChristine Van Broeckhoven
Christine Van Broeckhoven
Here we describe NanoPack, a set of tools developed for visualization and processing of long-read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences. The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools. Supplementary data are available at Bioinformatics online.
28 February 2019 in Nature Genetics
Verified
Journal Article
Closed access
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BKBrian W. Kunkle
Brian W. Kunkle
T(The European Alzheimer’s Disease Initiative (Eadi)
The European Alzheimer’s Disease Initiative (Eadi)
BGBenjamin Grenier-Boley
Benjamin Grenier-Boley
RSRebecca Sims
Rebecca Sims
JBJoshua C. Bis
Joshua C. Bis
MPMargaret A. Pericak-Vance
Margaret A. Pericak-Vance
4 April 2022 in Nature Genetics
Verified
Journal Article
Open access
PDF file
CBCéline Bellenguez
Céline Bellenguez
FKFahri Küçükali
Fahri Küçükali
IJIris E. Jansen
Iris E. Jansen
LKLuca Kleineidam
Luca Kleineidam
SMSonia Moreno-Grau
Sonia Moreno-Grau
JLJean-Charles Lambert
Jean-Charles Lambert
Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele.
17 July 2017 in Nature Genetics
Verified
Journal Article
Closed access
PDF file
RSRebecca Sims
Rebecca Sims
SLSven J van der Lee
Sven J van der Lee
ANAdam C Naj
Adam C Naj
CBCéline Bellenguez
Céline Bellenguez
NBNandini Badarinarayan
Nandini Badarinarayan
GSGerard D Schellenberg
Gerard D Schellenberg
1 May 2016 in Genetics in Medicine
Verified
Journal Article
Open access
CCCaroline Van Cauwenberghe
Caroline Van Cauwenberghe
CBChristine Van Broeckhoven
Christine Van Broeckhoven
KSKristel Sleegers
Kristel Sleegers
The search for the genetic factors contributing to Alzheimer disease (AD) has evolved tremendously throughout the years. It started from the discovery of fully penetrant mutations in Amyloid precursor protein, Presenilin 1, and Presenilin 2 as a cause of autosomal dominant AD, the identification of the ɛ4 allele of Apolipoprotein E as a strong genetic risk factor for both early-onset and late-onset AD, and evolved to the more recent detection of at least 21 additional genetic risk loci for the genetically complex form of AD emerging from genome-wide association studies and massive parallel resequencing efforts. These advances in AD genetics are positioned in light of the current endeavor directing toward translational research and personalized treatment of AD. We discuss the current state of the art of AD genetics and address the implications and relevance of AD genetics in clinical diagnosis and risk prediction, distinguishing between monogenic and multifactorial AD. Furthermore, the potential and current limitations of molecular reclassification of AD to streamline clinical trials in drug development and biomarker studies are addressed.Genet Med 18 5, 421-430.
23 March 2016 in Alzheimer's & Dementia
Verified
Journal Article
Open access
RCRita Cacace
Rita Cacace
KSKristel Sleegers
Kristel Sleegers
CBChristine Van Broeckhoven
Christine Van Broeckhoven
As the discovery of the Alzheimer's disease (AD) genes, APP, PSEN1, and PSEN2, in families with autosomal dominant early‐onset AD (EOAD), gene discovery in familial EOAD came more or less to a standstill. Only 5% of EOAD patients are carrying a pathogenic mutation in one of the AD genes or a apolipoprotein E (APOE) risk allele ε4, most of EOAD patients remain unexplained. Here, we aimed at summarizing the current knowledge of EOAD genetics and its role in ongoing approaches to understand the biology of AD and disease symptomatology as well as developing new therapeutics. Next, we explored the possible molecular mechanisms that might underlie the missing genetic etiology of EOAD and discussed how the use of massive parallel sequencing technologies triggered novel gene discoveries. To conclude, we commented on the relevance of reinvestigating EOAD patients as a means to explore potential new avenues for translational research and therapeutic discoveries.