Guidelines for investigating causality of sequence variants in human disease.

The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development.

GWAS for BMI: a treasure trove of fundamental insights into the genetic basis of obesity.

Muller et al. [1] have provided a strong critique of the Genome-Wide Association Studies (GWAS) of body-mass index (BMI), arguing that the GWAS approach for the study of BMI is flawed, and has provided us with few biological insights. They suggest that what is needed instead is a new start, involving GWAS for more complex energy balance related traits. In this invited counter-point, we highlight the substantial advances that have occurred in the obesity field, directly stimulated by the GWAS of BMI. We agree that GWAS for BMI is not perfect, but consider that the best route forward for additional discoveries will likely be to expand the search for common and rare variants linked to BMI and other easily obtained measures of obesity, rather than attempting to perform new, much smaller GWAS for energy balance traits that are complex and expensive to measure. For GWAS in general, we emphasise that the power from increasing the sample size of a crude but easily measured phenotype outweighs the benefits of better phenotyping.

A candidate gene approach to searching for low-penetrance breast and prostate cancer genes.

Most cases of breast and prostate cancer are not associated with mutations in known high-penetrance genes, indicating the involvement of multiple low-penetrance risk alleles. Studies that have attempted to identify these genes have met with limited success. The National Cancer Institute Breast and Prostate Cancer Cohort Consortium--a pooled analysis of multiple large cohort studies with a total of more than 5,000 cases of breast cancer and 8,000 cases of prostate cancer--was therefore initiated. The goal of this consortium is to characterize variations in approximately 50 genes that mediate two pathways that are associated with these cancers--the steroid-hormone metabolism pathway and the insulin-like growth factor signalling pathway--and to associate these variations with cancer risk.

Whole exome sequencing in a patient with uniparental disomy of chromosome 2 and a complex phenotype.

Whole exome sequencing and chromosomal microarrays are two powerful technologies that have transformed the ability of researchers to search for potentially causal variants in human disease. This study combines these tools to search for causal variants in a patient found to have maternal uniparental isodisomy of chromosome 2. This subject has a complex phenotype including skeletal and renal dysplasia, immune deficiencies, growth failure, retinal degeneration and ovarian insufficiency. Eighteen non-synonymous, rare homozygous variants were identified on chromosome 2. Additionally, five genes with compound heterozygous mutations were detected on other chromosomes that could lead to a disease phenotype independent of the uniparental disomy found in this case. Several candidate genes with potential connection to the phenotype are described but none are definitively proven to be causal. This study highlights the potential for detection of a large number of candidate genes using whole exome sequencing complicating interpretation in both the research and clinical settings. Forums must be created for publication and sharing of detailed phenotypic and genotypic reports to facilitate further biological discoveries and clinical counseling.

Large-scale discovery and genotyping of single-nucleotide polymorphisms in the mouse.

Single-nucleotide polymorphisms (SNPs) have been the focus of much attention in human genetics because they are extremely abundant and well-suited for automated large-scale genotyping. Human SNPs, however, are less informative than other types of genetic markers (such as simple-sequence length polymorphisms or microsatellites) and thus more loci are required for mapping traits. SNPs offer similar advantages for experimental genetic organisms such as the mouse, but they entail no loss of informativeness because bi-allelic markers are fully informative in analysing crosses between inbred strains. Here we report a large-scale analysis of SNPs in the mouse genome. We characterized the rate of nucleotide polymorphism in eight mouse strains and identified a collection of 2,848 SNPs located in 1,755 sequence-tagged sites (STSs) using high-density oligonucleotide arrays. Three-quarters of these SNPs have been mapped on the mouse genome, providing a first-generation SNP map of the mouse. We have also developed a multiplex genotyping procedure by which a genome scan can be performed with only six genotyping reactions per animal.

The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes.

Genetic association studies are viewed as problematic and plagued by irreproducibility. Many associations have been reported for type 2 diabetes, but none have been confirmed in multiple samples and with comprehensive controls. We evaluated 16 published genetic associations to type 2 diabetes and related sub-phenotypes using a family-based design to control for population stratification, and replication samples to increase power. We were able to confirm only one association, that of the common Pro12Ala polymorphism in peroxisome proliferator-activated receptor-gamma(PPARgamma) with type 2 diabetes. By analysing over 3,000 individuals, we found a modest (1.25-fold) but significant (P=0.002) increase in diabetes risk associated with the more common proline allele (85% frequency). Moreover, our results resolve a controversy about common variation in PPARgamma. An initial study found a threefold effect, but four of five subsequent publications failed to confirm the association. All six studies are consistent with the odds ratio we describe. The data implicate inherited variation in PPARgamma in the pathogenesis of type 2 diabetes. Because the risk allele occurs at such high frequency, its modest effect translates into a large population attributable risk-influencing as much as 25% of type 2 diabetes in the general population.

Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease: an exploratory study.

BACKGROUND: A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this exploratory investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing to identify potential blood-based biomarkers. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina's Infinium MethylationEPIC BeadChip arrays (n = 862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p ≤ × 10-8 and fold change ± 2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM. RESULTS: Top-ranked genes within which several dmCpGs were located and supported by functional data with methylation look-ups in other cohorts include: AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9 and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-ß signalling and Th17 cell differentiation. CONCLUSIONS: Epigenetic alterations provide a dynamic link between an individual's genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.

SPT3 is required for normal levels of a-factor and alpha-factor expression in Saccharomyces cerevisiae.

Mutations in the Saccharomyces cerevisiae SPT3 gene were previously found to cause suppression of Ty and delta insertion mutations in 5'-noncoding regions of genes. This suppression likely results from the fact that SPT3 is required for transcription initiation in delta sequences. Other additional phenotypes of spt3 mutants, including a mating defect, suggest that SPT3 is required for normal levels of expression of other genes. We analyzed the mating defect in spt3 mutants and showed that the levels of transcripts of the three major mating pheromone genes, MF alpha 1, MFa1, MFa2, were all reduced. The reduction in expression of these genes in spt3 mutants was not due to expression of a silent mating type cassette. Furthermore, we showed that the spt3 mating defect was manifest at the levels of both cellular fusion and nuclear fusion.

A new class of histone H2A mutations in Saccharomyces cerevisiae causes specific transcriptional defects in vivo.

Nucleosomes have been shown to repress transcription both in vitro and in vivo. However, the mechanisms by which this repression is overcome are only beginning to be understood. Recent evidence suggests that in the yeast Saccharomyces cerevisiae, many transcriptional activators require the SNF/SWI complex to overcome chromatin-mediated repression. We have identified a new class of mutations in the histone H2A-encoding gene HTA1 that causes transcriptional defects at the SNF/SWI-dependent gene SUC2. Some of the mutations are semidominant, and most of the predicted amino acid changes are in or near the N- and C-terminal regions of histone H2A. A deletion that removes the N-terminal tail of histone H2A also caused a decrease in SUC2 transcription. Strains carrying these histone mutations also exhibited defects in activation by LexA-GAL4, a SNF/SWI-dependent activator. However, these H2A mutants are phenotypically distinct from snf/swi mutants. First, not all SNF/SWI-dependent genes showed transcriptional defects in these histone mutants. Second, a suppressor of snf/swi mutations, spt6, did not suppress these histone mutations. Finally, unlike in snf/swi mutants, chromatin structure at the SUC2 promoter in these H2A mutants was in an active conformation. Thus, these H2A mutations seem to interfere with a transcription activation function downstream or independent of the SNF/SWI activity. Therefore, they may identify an additional step that is required to overcome repression by chromatin.

Variation in the clinical and genetic evaluation of undervirilized boys with bifid scrotum and hypospadias.

BACKGROUND: Bifid scrotum and hypospadias can be signs of undervirilization, yet boys presenting with these findings often do not undergo genetic evaluation. In some cases, identifying an underlying genetic diagnosis can help to optimize clinical care and improve guidance given to patients and families. OBJECTIVES: The aim of this study was to characterize current practice for genetic evaluation of patients with bifid scrotum, and to identify approaches with a good diagnostic yield. METHODS: A retrospective study of the Boston Children's Hospital electronic medical records (1993-2015) was conducted using the search term "bifid scrotum" and clinical data were extracted. Data were abstracted into a REDCap database for analysis. Statistical analysis was performed using SPSS, SAS, and Excel software. RESULTS: The search identified 110 subjects evaluated in the Urology and/or Endocrinology clinics for bifid scrotum. Genetic testing (including karyotype, microarray, or targeted testing) was performed on 64% of the subjects with bifid scrotum; of those tested, 23% (15% of the total cohort of 110 subjects) received a confirmed genetic diagnosis. Karyotype analysis, when performed, led to a diagnosis in 17% of patients. Of the ten instances when androgen receptor gene sequencing was performed, a pathogenic mutation was identified 20% of the time. CONCLUSION: This study demonstrated that the majority of individuals with moderate undervirilization resulting in bifid scrotum do not receive a genetic diagnosis. Over a third of the analyzed subjects did not have any genetic testing, even though karyotype analysis and androgen receptor (AR) sequencing were both relatively high yield for identifying a genetic etiology. Increased utilization of traditional genetic approaches could significantly improve the ability to find a genetic diagnosis.

Association testing of common variants in the insulin receptor substrate-1 gene (IRS1) with type 2 diabetes.

AIMS/HYPOTHESIS: Activation of the insulin receptor substrate-1 (IRS1) is a key initial step in the insulin signalling pathway. Despite several reports of association of the G972R polymorphism in its gene IRS1 with type 2 diabetes, we and others have not observed this association in well-powered samples. However, other nearby variants might account for the putative association signal. SUBJECTS AND METHODS: We characterised the haplotype map of IRS1 and selected 20 markers designed to capture common variations in the region. We genotyped this comprehensive set of markers in several family-based and case-control samples of European descent totalling 12,129 subjects. RESULTS: In an initial sample of 2,235 North American and Polish case-control pairs, the minor allele of the rs934167 polymorphism showed nominal evidence of association with type 2 diabetes (odds ratio [OR] 1.25, 95% CI 1.03-1.51, p = 0.03). This association showed a trend in the same direction in 7,659 Scandinavian samples (OR 1.16, 95% CI 0.96-1.39, p = 0.059). The combined OR was 1.20 (p = 0.008), but statistical correction for the number of variants examined yielded a p value of 0.086. We detected no differences across rs934167 genotypes in insulin-related quantitative traits. CONCLUSIONS/INTERPRETATION: Our data do not support an association of common variants in IRS1 with type 2 diabetes in populations of European descent.

Evidence that SNF2/SWI2 and SNF5 activate transcription in yeast by altering chromatin structure.

Changes in chromatin structure have frequently been correlated with changes in transcription. However, the cause-and-effect relationship between chromatin structure and transcription has been hard to determine. In addition, identifying the proteins that regulate chromatin structure has been difficult. Recent evidence suggests that a functionally related set of yeast transcriptional activators (SNF2/SWI2, SNF5, SNF6, SWI1, and SWI3), required for transcription of a diverse set of genes, may affect chromatin structure. We now present genetic and molecular evidence that at least two of these transcriptional activators, SNF2/SWI2 and SNF5, function by antagonizing repression mediated by nucleosomes. First, the transcriptional defects in strains lacking these SNF genes are suppressed by a deletion of one of the two sets of genes encoding histones H2A and H2B, (hta1-htb1) delta. Second, at one affected promoter (SUC2), chromatin structure is altered in snf2/swi2 and snf5 mutants, and this chromatin defect is suppressed by (hta1-htb1) delta. Finally, analysis of chromatin structure at a mutant SUC2 promoter, in which the TATA box has been destroyed, demonstrates that the differences in SUC2 chromatin structure between SNF5+ and snf5 mutant strains are not simply an effect of different levels of SUC2 transcription. Thus, these results strongly suggest that SNF2/SWI2 and SNF5 cause changes in chromatin structure and that these changes allow transcriptional activation.

SBE-TAGS: an array-based method for efficient single-nucleotide polymorphism genotyping.

Generating human single-nucleotide polymorphisms (SNPs) is no longer a rate-limiting step for genetic studies of disease. The number of SNPs in public databases already exceeds 200,000, and the total is expected to exceed 1,000,000 within a year. Rather, progress is limited by the inability to genotype large numbers of SNPs. Current genotyping methods are suitable for studying individual loci or at most a handful at a time. Here, we describe a method for parallel genotyping of SNPs, called single base extension-tag array on glass slides, SBE-TAGS. The principle is as follows. SNPs are genotyped by single base extension (SBE), using bifunctional primers carrying a unique sequence tag in addition to a locus-specific sequence. Because each locus has a distinct tag, the genotyping reactions can be performed in a highly multiplexed fashion, and the resulting product can then be "demultiplexed" by hybridization to the reverse complements of the sequence tags arrayed on a glass slide. SBE-TAGS is simple and inexpensive because of the high degree of multiplexing and the use of an easily generated, generic tag array. The method is also highly accurate: we genotyped over 100 SNPs, obtaining over 5, 000 genotypes, with approximately 99% accuracy.

Genomewide linkage analysis of stature in multiple populations reveals several regions with evidence of linkage to adult height.

Genomewide linkage analysis has been extremely successful at identification of the genetic variation underlying single-gene disorders. However, linkage analysis has been less successful for common human diseases and other complex traits in which multiple genetic and environmental factors interact to influence disease risk. We hypothesized that a highly heritable complex trait, in which the contribution of environmental factors was relatively limited, might be more amenable to linkage analysis. We therefore chose to study stature (adult height), for which heritability is approximately 75%-90% (Phillips and Matheny 1990; Carmichael and McGue 1995; Preece 1996; Silventoinen et al. 2000). We reanalyzed genomewide scans from four populations for which genotype and height data were available, using a variance-components method implemented in GENEHUNTER 2.0 (Pratt et al. 2000). The populations consisted of 408 individuals in 58 families from the Botnia region of Finland, 753 individuals in 183 families from other parts of Finland, 746 individuals in 179 families from Southern Sweden, and 420 individuals in 63 families from the Saguenay-Lac-St.-Jean region of Quebec. Four regions showed evidence of linkage to stature: 6q24-25, multipoint LOD score 3.85 at marker D6S1007 in Botnia (genomewide P<.06), 7q31.3-36 (LOD 3.40 at marker D7S2195 in Sweden, P<.02), 12p11.2-q14 (LOD 3.35 at markers D12S10990-D12S398 in Finland, P<.05) and 13q32-33 (LOD 3.56 at markers D13S779-D13S797 in Finland, P<.05). In a companion article (Perola et al. 2001 [in this issue]), strong supporting evidence is obtained for linkage to the region on chromosome 7. These studies suggest that highly heritable complex traits such as stature may be genetically tractable and provide insight into the genetic architecture of complex traits.