Supplementary Material for: Joint linkage and association analysis using GENEHUNTER-MODSCORE with an application to familial pancreatic cancer

Introduction: Joint linkage and association (JLA) analysis combines two disease gene mapping strategies: linkage information contained in families and association information contained in populations. Such a JLA analysis can increase mapping power, especially when the evidence for both linkage and association is low to moderate. Similarly, an association analysis based on haplotypes instead of single markers can increase mapping power when the association pattern is complex. Methods: In this paper, we present an extension to the GENEHUNTER-MODSCORE software package that enables a JLA analysis based on haplotypes and uses information from arbitrary pedigree types and unrelated individuals. Our new JLA method is an extension of the MOD score approach for linkage analysis, which allows the estimation of trait-model and linkage disequilibrium (LD) parameters, i.e., penetrance, disease-allele frequency, and haplotype frequencies. LD is modelled between alleles at a single diallelic disease locus and up to three diallelic test markers. Linkage information is contributed by additional multi-allelic flanking markers. We investigated the statistical properties of our JLA implementation using extensive simulations, and we compared our approach to another commonly used single-marker JLA test. To demonstrate the applicability of our new method in practice, we analyzed pedigree data from the German National Case Collection for Familial Pancreatic Cancer (FaPaCa). Results: Based on the simulated data, we demonstrated the validity of our JLA MOD score analysis implementation and identified scenarios in which haplotype-based tests outperformed the single-marker test. The estimated trait-model and LD parameters were in good accordance with the simulated values. Our method outperformed another commonly used JLA single-marker test when the LD pattern was complex. The exploratory analysis of the FaPaCa families led to the identification of a promising genetic region on chromosome 22q13.33, which can serve as a starting point for future mutation analysis and molecular research in pancreatic cancer. Conclusion: Our newly proposed JLA MOD score method proves to be a valuable gene mapping and characterization tool, especially when either linkage or association information alone provide insufficient power to identify the disease-causing genetic variants

Supplementary Material for: Loss of Chromosome 18 in Neuroendocrine Tumors of the Small Intestine: The Enigma Remains

<p><b><i>Background/Aims:</i></b> Neuroendocrine tumors of the small intestine (SI-NETs) exhibit an increasing incidence and high mortality rate. Until now, no fundamental molecular event has been linked to the tumorigenesis and progression of these tumors. Only the loss of chromosome 18 (Chr18) has been shown in up to two thirds of SI-NETs, whereby the significance of this alteration is still not understood. We therefore performed the first comprehensive study to identify Chr18-related events at the genetic, epigenetic and gene/protein expression levels. <b><i>Methods:</i></b> We did expression analysis of all seven putative Chr18-related tumor suppressors by quantitative real-time PCR (qRT-PCR), Western blot and immunohistochemistry. Next-generation exome sequencing and SNP array analysis were performed with five SI-NETs with (partial) loss of Chr18. Finally, we analyzed all microRNAs (miRNAs) located on Chr18 by qRT-PCR, comparing Chr18+/- and Chr18+/+ SI-NETs. <b><i>Results:</i></b> Only DCC (deleted in colorectal cancer) revealed loss of/greatly reduced expression in 6/21 cases (29%). No relevant loss of SMAD2, SMAD4, elongin A3 and CABLES was detected. PMAIP1 and maspin were absent at the protein level. Next-generation sequencing did not reveal relevant recurrent somatic mutations on Chr18 either in an exploratory cohort of five SI-NETs, or in a validation cohort (n = 30). SNP array analysis showed no additional losses. The quantitative analysis of all 27 Chr18-related miRNAs revealed no difference in expression between Chr18+/- and Chr18+/+ SI-NETs. <b><i>Conclusion:</i></b> DCC seems to be the only Chr18-related tumor suppressor affected by the monoallelic loss of Chr18 resulting in a loss of DCC protein expression in one third of SI-NETs. No additional genetic or epigenetic alterations were present on Chr18.</p