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Clonal mosaicism for large chromosomal anomalies (duplications, deletions and uniparental disomy) was detected using SNP microarray data from over 50,000 subjects recruited for genome-wide association studies. This detection method requires a relatively high frequency of cells (>5–10%) with the same abnormal karyotype (presumably of clonal origin) in the presence of normal cells. The frequency of detectable clonal mosaicism in peripheral blood is low (

Genotyping experiments are widely used in clinical and basic research laboratories to identify associations between genetic variations and normal/abnormal phenotypes. Genotyping assay techniques vary from single genomic regions that are interrogated using PCR reactions to high throughput assays examining genome-wide sequence and structural variation. The resulting genotype data may include millions of markers of thousands of individuals, requiring various statistical, modeling or other data analysis methodologies to interpret the results. To date, there are no standards for reporting genotyping experiments. Here we present the Minimum Information about a Genotyping Experiment (MIGen) standard, defining the minimum information required for reporting genotyping experiments. MIGen standard covers experimental design, subject description, genotyping procedure, quality control and data analysis. MIGen is a registered project under MIBBI (Minimum Information for Biological and Biomedical Investigations) and is being developed by an interdisciplinary group of experts in basic biomedical science, clinical science, biostatistics and bioinformatics. To accommodate the wide variety of techniques and methodologies applied in current and future genotyping experiment, MIGen leverages foundational concepts from the Ontology for Biomedical Investigations (OBI) for the description of the various types of planned processes and implements a hierarchical document structure. The adoption of MIGen by the research community will facilitate consistent genotyping data interpretation and independent data validation. MIGen can also serve as a framework for the development of data models for capturing and storing genotyping results and experiment metadata in a structured way, to facilitate the exchange of metadata.

White blood cell count (WBC) is unique among identified inflammatory predictors of chronic disease in that it is routinely measured in asymptomatic patients in the course of routine patient care. We led a genome-wide association analysis to identify variants associated with WBC levels in 13,923 subjects in the electronic Medical Records and Genomics (eMERGE) Network. We identified two regions of interest that were each unique to subjects of genetically determined ancestry to the African continent (AA) or to the European continent (EA). WBC varies among different ancestry groups. Despite being ancestry specific, these regions were identifiable in the combined analysis. In AA subjects, the region surrounding the Duffy antigen/chemokine receptor gene (DARC) on 1q21 exhibited significant association (p value = 6.71e–55). These results validate the previously reported association between WBC and of the regulatory variant rs2814778 in the promoter region, which causes the Duffy negative phenotype (Fy−/−). A second missense variant (rs12075) is responsible for the two principal antigens, Fya and Fyb of the Duffy blood group system. The two variants, consisting of four alleles, act in concert to produce five antigens and subsequent phenotypes. We were able to identify the marginal and novel interaction effects of these two variants on WBC. In the EA subjects, we identified significantly associated SNPs tagging three separate genes in the 17q21 region: (1) GSDMA, (2) MED24, and (3) PSMD3. Variants in this region have been reported to be associated with WBC, neutrophil count, and inflammatory diseases including asthma and Crohn’s disease.

A genome-wide association study was carried out in 1020 case subjects with recurrent early-onset major depressive disorder (MDD) (onset before age 31) and 1636 control subjects screened to exclude lifetime MDD. Subjects were genotyped with the Affymetrix 6.0 platform. After extensive quality control procedures, 671 424 autosomal single nucleotide polymorphisms (SNPs) and 25 068 X chromosome SNPs with minor allele frequency greater than 1% were available for analysis. An additional 1 892 186 HapMap II SNPs were analyzed based on imputed genotypic data. Single-SNP logistic regression trend tests were computed, with correction for ancestry-informative principal component scores. No genome-wide significant evidence for association was observed, assuming that nominal P5 × 10(-8) approximates a 5% genome-wide significance threshold. The strongest evidence for association was observed on chromosome 18q22.1 (rs17077540, P=1.83 × 10(-7)) in a region that has produced some evidence for linkage to bipolar-I or -II disorder in several studies, within an mRNA detected in human brain tissue (BC053410) and approximately 75 kb upstream of DSEL. Comparing these results with those of a meta-analysis of three MDD GWAS data sets reported in a companion article, we note that among the strongest signals observed in the GenRED sample, the meta-analysis provided the greatest support (although not at a genome-wide significant level) for association of MDD to SNPs within SP4, a brain-specific transcription factor. Larger samples will be required to confirm the hypothesis of association between MDD (and particularly the recurrent early-onset subtype) and common SNPs.

We have investigated the association of multiple sclerosis (MS) with polymorphisms in the IL4R gene in 332 single-case MS families. IL4R encodes a subunit of the interleukin-4 receptor, a molecule important for T-cell development and differentiation, and is a gene shown to be associated with immune-related diseases such as asthma and type I diabetes. By genotyping two promoter and eight coding IL4R SNPs and identifying haplotypes (complex alleles) in the MS families, stratified for HLA genotype, we have observed evidence of the association of the IL4R gene to MS. In particular, we have identified a specific susceptibility haplotype, and observe that the risk is conferred primarily to individuals not carrying the high MS-risk HLA DR2 (DRB1(*)1501-DQB1(*)0602) haplotype (nominal P=0.009). These findings suggest a potentially important role for the IL4R gene in predisposition to MS, and provide further evidence of its relevance as a candidate gene for immune-related diseases.

Correction to: Molecular Psychiatry advance online publication, 14 August 2012; doi:10.1038/mp.2012.85 The name of coauthor LK Davis was omitted from the author line. Dr Davis should have been listed as the tenth author (between ER Gamazon and L Osiecki). Her affiliation is as follows: Department ofMedicine, University of Chicago, Chicago, IL, USA.

Recommendations and guidance on how to handle the return of genetic results to patients have offered limited insight into how to approach incidental genetic findings in the context of clinical trials. This paper provides the Genomics and Randomized Trials Network (GARNET) recommendations on incidental genetic findings in the context of clinical trials, and discusses the ethical and practical issues considered in formulating our recommendations. There are arguments in support of as well as against returning incidental genetic findings in clinical trials. For instance, reporting incidental findings in clinical trials may improve the investigator-participant relationship and the satisfaction of participation, but it may also blur the line between clinical care and research. The issues of whether and how to return incidental genetic findings, including the costs of doing so, should be considered when developing clinical trial protocols. Once decided, plans related to sharing individual results from the aim(s) of the trial, as well as incidental findings, should be discussed explicitly in the consent form. Institutional Review Boards (IRBs) and other study-specific governing bodies should be part of the decision as to if, when, and how to return incidental findings, including when plans in this regard are being reconsidered.