Roderick H. J. Houwen

Bio: Roderick H. J. Houwen is an academic researcher from Utrecht University. The author has contributed to research in topics: Cholestasis & Progressive familial intrahepatic cholestasis. The author has an hindex of 51, co-authored 189 publications receiving 9810 citations. Previous affiliations of Roderick H. J. Houwen include University Medical Center Utrecht & Boston Children's Hospital.

Multiple common variants for celiac disease influencing immune gene expression

Abstract: We performed a second-generation genome-wide association study of 4,533 individuals with celiac disease (cases) and 10,750 control subjects. We genotyped 113 selected SNPs with P(GWAS) < 10(-4) and 18 SNPs from 14 known loci in a further 4,918 cases and 5,684 controls. Variants from 13 new regions reached genome-wide significance (P(combined) < 5 x 10(-8)); most contain genes with immune functions (BACH2, CCR4, CD80, CIITA-SOCS1-CLEC16A, ICOSLG and ZMIZ1), with ETS1, RUNX3, THEMIS and TNFRSF14 having key roles in thymic T-cell selection. There was evidence to suggest associations for a further 13 regions. In an expression quantitative trait meta-analysis of 1,469 whole blood samples, 20 of 38 (52.6%) tested loci had celiac risk variants correlated (P < 0.0028, FDR 5%) with cis gene expression.

Multiple common variants for celiac disease influencing immune gene expression

Abstract: We performed a second-generation genome-wide association study of 4,533 individuals with celiac disease (cases) and 10,750 control subjects. We genotyped 113 selected SNPs with P(GWAS) < 10(-4) and 18 SNPs from 14 known loci in a further 4,918 cases and 5,684 controls. Variants from 13 new regions reached genome-wide significance (P(combined) < 5 x 10(-8)); most contain genes with immune functions (BACH2, CCR4, CD80, CIITA-SOCS1-CLEC16A, ICOSLG and ZMIZ1), with ETS1, RUNX3, THEMIS and TNFRSF14 having key roles in thymic T-cell selection. There was evidence to suggest associations for a further 13 regions. In an expression quantitative trait meta-analysis of 1,469 whole blood samples, 20 of 38 (52.6%) tested loci had celiac risk variants correlated (P < 0.0028, FDR 5%) with cis gene expression.

EASL Clinical Practice Guidelines: Wilson's disease

Abstract: This Clinical Practice Guideline (CPG) has been developed to assist physicians and other healthcare providers in the diagnosis and management of patients with Wilson's disease. The goal is to describe a number of generally accepted approaches for diagnosis, prevention, and treatment of Wilson's disease. Recommendations are based on a systematic literature review in the Medline (PubMed version), Embase (Dialog version), and the Cochrane Library databases using entries from 1966 to 2011. The Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system used in other EASL CPGs was used and set against the somewhat different grading system used in the AASLD guidelines (Table 1A and B). Unfortunately, there is not a single randomized controlled trial conducted in Wilson's disease which has an optimal design. Thus, it is impossible to assign a high or even a moderate quality of evidence to any of the questions dealt with in these guidelines. The evaluation is mostly based on large case series which have been reported within the last decades.

A gene encoding a P-type ATPase mutated in two forms of hereditary cholestasis.

Abstract: Cholestasis, or impaired bile flow, is an important but poorly understood manifestation of liver disease. Two clinically distinct forms of inherited cholestasis, benign recurrent intrahepatic cholestasis (BRIC) and progressive familial intrahepatic cholestasis type 1 (PFIC1), were previously mapped to 18q21. Haplotype analysis narrowed the candidate region for both diseases to the same interval of less than 1 cM, in which we identified a gene mutated in BRIC and PFIC1 patients. This gene (called FIC1) is the first identified human member of a recently described subfamily of P-type ATPases; ATP-dependent aminophospholipid transport is the previously described function of members of this subfamily. FIC1 is expressed in several epithelial tissues and, surprisingly, more strongly in small intestine than in liver. Its protein product is likely to play an essential role in enterohepatic circulation of bile acids; further characterization of FIC1 will facilitate understanding of normal bile formation and cholestasis.

Characterizing responses to CFTR-modulating drugs using rectal organoids derived from subjects with cystic fibrosis

Abstract: Identifying subjects with cystic fibrosis (CF) who may benefit from cystic fibrosis transmembrane conductance regulator (CFTR)-modulating drugs is time-consuming, costly, and especially challenging for individuals with rare uncharacterized CFTR mutations. We studied CFTR function and responses to two drugs-the prototypical CFTR potentiator VX-770 (ivacaftor/KALYDECO) and the CFTR corrector VX-809 (lumacaftor)-in organoid cultures derived from the rectal epithelia of subjects with CF, who expressed a broad range of CFTR mutations. We observed that CFTR residual function and responses to drug therapy depended on both the CFTR mutation and the genetic background of the subjects. In vitro drug responses in rectal organoids positively correlated with published outcome data from clinical trials with VX-809 and VX-770, allowing us to predict from preclinical data the potential for CF patients carrying rare CFTR mutations to respond to drug therapy. We demonstrated proof of principle by selecting two subjects expressing an uncharacterized rare CFTR genotype (G1249R/F508del) who showed clinical responses to treatment with ivacaftor and one subject (F508del/R347P) who showed a limited response to drug therapy both in vitro and in vivo. These data suggest that in vitro measurements of CFTR function in patient-derived rectal organoids may be useful for identifying subjects who would benefit from CFTR-correcting treatment, independent of their CFTR mutation.

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

Abstract: Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.

A second generation human haplotype map of over 3.1 million SNPs

Abstract: We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.

Five years of GWAS discovery

Abstract: The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section.

Singular Value Decomposition for Genome-Wide Expression Data Processing and Modeling

Abstract: ‡We describe the use of singular value decomposition in transforming genome-wide expression data from genes 3 arrays space to reduced diagonalized ‘‘eigengenes’’ 3 ‘‘eigenarrays’’ space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.