Gerard A. Bouland
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View article: Genetic modulation of immune gene co-expression in the aged mouse hippocampus by the <i>Apbb1ip</i> locus
Genetic modulation of immune gene co-expression in the aged mouse hippocampus by the <i>Apbb1ip</i> locus Open
Ageing is a major risk factor for many neurodegenerative diseases, and the hippocampus is particularly vulnerable to the effects of ageing. To define the transcriptomic changes related to ageing and the impact of genetic variation, we anal…
View article: scAGG: Sample-level embedding and classification of Alzheimer's disease from single-nucleus data
scAGG: Sample-level embedding and classification of Alzheimer's disease from single-nucleus data Open
Identifying key cell types and genes in Alzheimer's Disease (AD) is crucial for understanding its pathogenesis and discovering therapeutic targets. Single-cell RNA sequencing technology (scRNAseq) has provided unprecedented opportunities t…
View article: gsQTL: Associating genetic risk variants with gene sets by exploiting their shared variability
gsQTL: Associating genetic risk variants with gene sets by exploiting their shared variability Open
To investigate the functional significance of genetic risk loci identified through genome-wide association studies (GWASs), genetic loci are linked to genes based on their capacity to account for variation in gene expression, resulting in …
View article: Small RNA sequencing reveals snoRNAs and piRNA-019825 as novel players in diabetic kidney disease
Small RNA sequencing reveals snoRNAs and piRNA-019825 as novel players in diabetic kidney disease Open
Introduction Micro- and macrovascular complications are common among persons with type 2 diabetes. Recently there has been growing interest to investigate the potential of circulating small non-coding RNAs (sncRNAs) as contributors to the …
View article: An omics-based machine learning approach to predict diabetes progression: a RHAPSODY study
An omics-based machine learning approach to predict diabetes progression: a RHAPSODY study Open
Aims/hypothesis People with type 2 diabetes are heterogeneous in their disease trajectory, with some progressing more quickly to insulin initiation than others. Although classical biomarkers such as age, HbA 1c and diabetes duration are as…
View article: Single-cell RNA sequencing data reveals rewiring of transcriptional relationships in Alzheimer’s Disease associated with risk variants
Single-cell RNA sequencing data reveals rewiring of transcriptional relationships in Alzheimer’s Disease associated with risk variants Open
Understanding how genetic risk variants contribute to Alzheimer’s Disease etiology remains a challenge. Single-cell RNA sequencing (scRNAseq) allows for the investigation of cell type specific effects of genomic risk loci on gene expressio…
View article: Identification of biomarkers for glycaemic deterioration in type 2 diabetes
Identification of biomarkers for glycaemic deterioration in type 2 diabetes Open
We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triac…
View article: Identifying Aging and Alzheimer Disease–Associated Somatic Variations in Excitatory Neurons From the Human Frontal Cortex
Identifying Aging and Alzheimer Disease–Associated Somatic Variations in Excitatory Neurons From the Human Frontal Cortex Open
Our results show that combining scRNA-seq and WGS data can successfully detect putative somatic mutations. The putative somatic mutations detected from ROSMAP data set have provided new insights into the association of AD and aging with br…
View article: Consequences and opportunities arising due to sparser single-cell RNA-seq datasets
Consequences and opportunities arising due to sparser single-cell RNA-seq datasets Open
View article: Identifying aging and Alzheimer’s disease associated somatic mutations in excitatory neurons from the human frontal cortex using whole genome sequencing and single cell RNA sequencing data
Identifying aging and Alzheimer’s disease associated somatic mutations in excitatory neurons from the human frontal cortex using whole genome sequencing and single cell RNA sequencing data Open
With age, somatic mutations accumulated in human brain cells can lead to various neurological disorders and brain tumors. Since the incidence rate of Alzheimer’s disease (AD) increases exponentially with age, investigating the association …
View article: Small RNA sequencing reveals snoRNAs and piRNA-019825 as novel players in diabetic kidney disease
Small RNA sequencing reveals snoRNAs and piRNA-019825 as novel players in diabetic kidney disease Open
Introduction Micro- and macrovascular complications are common among persons with type 2 diabetes. Recently there has been growing interest to investigate the potential of circulating small non-coding RNAs (sncRNAs) as contributors to the …
View article: The rise of sparser single-cell RNAseq datasets; consequences and opportunities
The rise of sparser single-cell RNAseq datasets; consequences and opportunities Open
There is an exponential increase in the number of cells measured in single-cell RNA sequencing (scRNAseq) datasets. Concurrently, scRNA-seq datasets become increasingly sparser as more zero counts are measured for many genes. We discuss th…
View article: Diabetes risk loci-associated pathways are shared across metabolic tissues
Diabetes risk loci-associated pathways are shared across metabolic tissues Open
View article: Additional file 7 of Diabetes risk loci-associated pathways are shared across metabolic tissues
Additional file 7 of Diabetes risk loci-associated pathways are shared across metabolic tissues Open
Additional file 7: Table S6. Enriched REACTOME pathways based on T2D SNPs.
View article: Additional file 6 of Diabetes risk loci-associated pathways are shared across metabolic tissues
Additional file 6 of Diabetes risk loci-associated pathways are shared across metabolic tissues Open
Additional file 6: Table S5. Enriched KEGG pathways based on T2D SNPs.
View article: Additional file 3 of Diabetes risk loci-associated pathways are shared across metabolic tissues
Additional file 3 of Diabetes risk loci-associated pathways are shared across metabolic tissues Open
Additional file 3: Table S2. eQTLs associated with T2D SNPs.
View article: Differential analysis of binarized single-cell RNA sequencing data captures biological variation
Differential analysis of binarized single-cell RNA sequencing data captures biological variation Open
Single-cell RNA sequencing data is characterized by a large number of zero counts, yet there is growing evidence that these zeros reflect biological variation rather than technical artifacts. We propose to use binarized expression profiles…
View article: Distinct Molecular Signatures of Clinical Clusters in People with Type 2 Diabetes: an IMI-RHAPSODY Study
Distinct Molecular Signatures of Clinical Clusters in People with Type 2 Diabetes: an IMI-RHAPSODY Study Open
Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity a previous study clustered people with diabetes into five diabetes subtypes. The aim of the current study is to investigate the…
View article: Distinct Molecular Signatures of Clinical Clusters in People with Type 2 Diabetes: an IMI-RHAPSODY Study
Distinct Molecular Signatures of Clinical Clusters in People with Type 2 Diabetes: an IMI-RHAPSODY Study Open
Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity a previous study clustered people with diabetes into five diabetes subtypes. The aim of the current study is to investigate the…
View article: Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study
Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study Open
Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current s…
View article: Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study
Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study Open
View article: Novel biomarkers for glycaemic deterioration in type 2 diabetes: an IMI RHAPSODY study
Novel biomarkers for glycaemic deterioration in type 2 diabetes: an IMI RHAPSODY study Open
We have deployed a multi-omics approach in large cohorts of patients with existing type 2 diabetes to identify biomarkers for disease progression across three molecular classes, metabolites, lipids and proteins. A Cox regression analysis f…
View article: Differential dropout analysis captures biological variation in single-cell RNA sequencing data
Differential dropout analysis captures biological variation in single-cell RNA sequencing data Open
Single-cell RNA sequencing data is characterized by a large number of zero counts, yet there is growing evidence that these zeros reflect biological variation rather than technical artifacts. We propose differential dropout analysis (DDA) …
View article: Differential analysis of binarized single-cell RNA sequencing data captures biological variation
Differential analysis of binarized single-cell RNA sequencing data captures biological variation Open
Processed datasets used for binary differential analysis experiments.
View article: Differential analysis of binarized single-cell RNA sequencing data captures biological variation
Differential analysis of binarized single-cell RNA sequencing data captures biological variation Open
Processed datasets used for binary differential analysis experiments.
View article: Replication and cross-validation of T2D subtypes based on clinical variables: an IMI-RHAPSODY study
Replication and cross-validation of T2D subtypes based on clinical variables: an IMI-RHAPSODY study Open
Aims/hypothesis Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes (T2D). In the current study we replicate and cross-validate these T2D clusters in…
View article: CONQUER: an interactive toolbox to understand functional consequences of GWAS hits
CONQUER: an interactive toolbox to understand functional consequences of GWAS hits Open
Numerous large genome-wide association studies have been performed to understand the influence of genetics on traits. Many identified risk loci are in non-coding and intergenic regions, which complicates understanding how genes and their d…
View article: Understanding functional consequences of type 2 diabetes risk loci using the universal data integration and visualization R package CONQUER
Understanding functional consequences of type 2 diabetes risk loci using the universal data integration and visualization R package CONQUER Open
Background Numerous large genome-wide association studies (GWASs) have been performed to understand the genetic factors of numerous traits, including type 2 diabetes. Many identified risk loci are located in non-coding and intergenic regio…
View article: <i>NACHO:</i> an R package for quality control of NanoString nCounter data
<i>NACHO:</i> an R package for quality control of NanoString nCounter data Open
Summary The NanoStringTM nCounter® is a platform for the targeted quantification of expression data in biofluids and tissues. While software by the manufacturer is available in addition to third parties packages, they do not provide a comp…