Kathi C. Huddleston

Germline variation in cancer-susceptibility genes in a healthy, ancestrally diverse cohort: implications for individual genome sequencing.

Technological advances coupled with decreasing costs are bringing whole genome and whole exome sequencing closer to routine clinical use. One of the hurdles to clinical implementation is the high number of variants of unknown significance. For cancer-susceptibility genes, the difficulty in interpreting the clinical relevance of the genomic variants is compounded by the fact that most of what is known about these variants comes from the study of highly selected populations, such as cancer patients or individuals with a family history of cancer. The genetic variation in known cancer-susceptibility genes in the general population has not been well characterized to date. To address this gap, we profiled the nonsynonymous genomic variation in 158 genes causally implicated in carcinogenesis using high-quality whole genome sequences from an ancestrally diverse cohort of 681 healthy individuals. We found that all individuals carry multiple variants that may impact cancer susceptibility, with an average of 68 variants per individual. Of the 2,688 allelic variants identified within the cohort, most are very rare, with 75% found in only 1 or 2 individuals in our population. Allele frequencies vary between ancestral groups, and there are 21 variants for which the minor allele in one population is the major allele in another. Detailed analysis of a selected subset of 5 clinically important cancer genes, BRCA1, BRCA2, KRAS, TP53, and PTEN, highlights differences between germline variants and reported somatic mutations. The dataset can serve a resource of genetic variation in cancer-susceptibility genes in 6 ancestry groups, an important foundation for the interpretation of cancer risk from personal genome sequences.

New observations on maternal age effect on germline de novo mutations

Germline mutations are the source of evolution and contribute substantially to many health-related processes. Here we use whole-genome deep sequencing data from 693 parents–offspring trios to examine the de novo point mutations (DNMs) in the offspring. Our estimate for the mutation rate per base pair per generation is 1.05 × 10−8, well within the range of previous studies. We show that maternal age has a small but significant correlation with the total number of DNMs in the offspring after controlling for paternal age (0.51 additional mutations per year, 95% CI: 0.29, 0.73), which was not detectable in the smaller and younger parental cohorts of earlier studies. Furthermore, while the total number of DNMs increases at a constant rate for paternal age, the contribution from the mother increases at an accelerated rate with age.These observations have implications related to the incidence of de novo mutations relating to maternal age.

Utility of whole-genome sequencing for detection of newborn screening disorders in a population cohort of 1,696 neonates

Purpose:To assess the potential of whole-genome sequencing (WGS) to replicate and augment results from conventional blood-based newborn screening (NBS).Methods:Research-generated WGS data from an ancestrally diverse cohort of 1,696 infants and both parents of each infant were analyzed for variants in 163 genes involved in disorders included or under discussion for inclusion in US NBS programs. WGS results were compared with results from state NBS and related follow-up testing.Results:NBS genes are generally well covered by WGS. There is a median of one (range: 0–6) database-annotated pathogenic variant in the NBS genes per infant. Results of WGS and NBS in detecting 28 state-screened disorders and four hemoglobin traits were concordant for 88.6% of true positives (n = 35) and 98.9% of true negatives (n = 45,757). Of the five infants affected with a state-screened disorder, WGS identified two whereas NBS detected four. WGS yielded fewer false positives than NBS (0.037 vs. 0.17%) but more results of uncertain significance (0.90 vs. 0.013%).Conclusion:WGS may help rule in and rule out NBS disorders, pinpoint molecular diagnoses, and detect conditions not amenable to current NBS assays.Genet Med 18 3, 221–230.

Aberrant splicing induced by the most common EPG5 mutation in an individual with Vici syndrome

Sir, Recently, a study describing the clinical and genetic data of 50 patients (30 families) with Vici syndrome (OMIM 242840) was published in Brain (Byrne et al. , 2016 b ). Vici syndrome is a severe autosomal recessive condition recently found to be caused by mutations in the EPG5 gene (NG_042838.1) (Cullup et al. , 2013). Principal features of Vici syndrome include neurological sequelae (agenesis of the corpus callosum, profound developmental delay, and progressive microcephaly), neonatal cataracts, hypopigmentation involving both skin and hair, progressive dilated or hypertrophic cardiomyopathy, and both B and T cell-related immunodeficiency (Byrne et al. , 2016 a , b ). The most common mutation identified in Vici syndrome patients is EPG5 NM_020964.2; c.1007A>G p.Gln336Arg. Based on the two large cohorts of patients recently studied (Cullup et al. , 2013; Byrne et al. , 2016 b ), this mutation accounts for >10% (9/86) of mutations. Ancestry data from previous studies show that this mutation may be associated with Ashkenazi descent (Byrne et al. , 2016 a , b ). This variant was not detected in whole genome sequencing data from our cohort of 4456 unrelated adults seen at the Inova Translational Medicine Institute (Bodian et al. , 2014, 2016). This variant is seen with a frequency of 3.129 ×10−5 in the European (non-Finnish) population of Exome Aggregation Consortium (ExAC) and has thus far never been reported in other ExAC populations (ExAC, 2016; http://exac.broadinstitute.org). The EGP5 c.1007A>G mutation has been suggested to affect splicing through in silico prediction models, though multiple predictions are contradictory [Human Splicing Finder (Desmet et al. , 2009; http://www.umd.be/HSF3/HSF.html: −6%) and NNSPLICE (Reese et al. , 1997; http://www.fruitfly.org/seq_tools/splice.html: −100%)]. Likewise, in silico predictions of the missense mutation are in disagreement with regards to its pathogenicity [PolyPhen-2 (Adzhubei et al. , …

Utilization of genomic sequencing for population screening of immunodeficiencies in the newborn

PurposeImmunodeficiency screening has been added to many state-directed newborn screening programs. The current methodology is limited to screening for severe T-cell lymphopenia disorders. We evaluated the potential of genomic sequencing to augment current newborn screening for immunodeficiency, including identification of non–T cell disorders.MethodsWe analyzed whole-genome sequencing (WGS) and clinical data from a cohort of 1,349 newborn–parent trios by genotype-first and phenotype-first approaches. For the genotype-first approach, we analyzed predicted protein-impacting variants in 329 immunodeficiency-related genes in the WGS data. As a phenotype-first approach, electronic health records were used to identify children with clinical features suggestive of immunodeficiency. Genomes of these children and their parents were analyzed using a separate pipeline for identification of candidate pathogenic variants for rare Mendelian disorders.ResultsWGS provides adequate coverage for most known immunodeficiency-related genes. 13,476 distinct variants and 8,502 distinct predicted protein-impacting variants were identified in this cohort; five individuals carried potentially pathogenic variants requiring expert clinical correlation. One clinically asymptomatic individual was found genomically to have complement component 9 deficiency. Of the symptomatic children, one was molecularly identified as having an immunodeficiency condition and two were found to have other molecular diagnoses.ConclusionNeonatal genomic sequencing can potentially augment newborn screening for immunodeficiency.

Investigating the accuracy of parentally reported weights and lengths at 12 months of age as compared to measured weights and lengths in a longitudinal childhood genome study

Background Childhood obesity studies rely on parentally reported anthropometrics. However, the accuracy of such data has not been evaluated for 12-month-old children. Moreover, methods to improve the accuracy of reported data have not been assessed in prior studies. Methods A total of 185 children enrolled in a northern Virginia childhood longitudinal cohort genomic study had parentally completed surveys at 12 months. Measured weights and lengths were recorded for the same children from their 12-month paediatrician visit. Weight for length percentiles were calculated using World Health Organization gender-specific growth charts. The agreement between reported and measured values was examined using Pearsons correlation, paired t-test and κ statistics. The interquartile outlier rule was used to detect and remove outliers. Results Parentally reported weight was strongly associated with measured weight at 12 months (r=0.90). There was only a moderate correlation between parentally reported and measured lengths (r=0.52) and calculated weight for length percentiles (r=0.65). After removing outliers from parentally reported data, there was an increase in correlation between parentally reported and measured data for weight (r=0.93), length (r=0.69) and weight for length percentiles (r=0.76). Outliers removed compared to all children included were more likely to have maternal education less than a bachelors degree (p=0.007). Conclusions After removal of outliers from reported data, there is a strong correlation between calculated reported and measured weight for length percentiles suggesting that this may be an effective method to increase accuracy when conducting large-scale obesity studies in young children where study costs benefit from using parentally reported data.

Clinical, Social, and Genetic Factors Associated with Obesity at 12 Months of Age

Objective To examine genomic, social, and clinical risk factors of ≥85 weight for length percentile (WFLP) at 12 months. Study design Children in this study had whole‐genome sequencing, and clinical and social data were collected. WFLPs at 12 months of age were grouped as follows: (1) <85th, (2) ≥85th to <95th, (3) ≥95th to <99th, and (4) ≥99th. Whole‐genome sequencing data were used to analyze rare and common variants, and association of clinical and social factors was examined. Results A total of 690 children were included; WFLPs were 422 (61.2%) <85th, 112 (16.2%) ≥85th‐<95th, 89 (12.9%) ≥95th‐<99th, and 67 (9.7%) ≥99th. Family‐related risk factors associated with greater WFLP were greater paternal body mass index, WFLP ≥99th OR 1.10 (1.03‐1.16), and greater than recommended weight gain in pregnancy, WFLP ≥85th‐<95th OR 1.90 (1.09‐3.26). More breast milk at 6 months was protective factor: WFLP ≥85th‐<95th, OR 0.98 (0.97‐0.99), WFLP ≥95th‐<99th OR 0.98 (0.97‐0.99), and WFLP ≥99th OR 0.98 (0.96‐0.99). Although none of the variants reached genome‐wide significance, there was a trend toward increased prevalence of genetic variants within or near genes previously associated with obesity in children with WFLP ≥99th. Conclusion This cross‐sectional study identified several modifiable factors, including increased weight gain in pregnancy and decreased breast milk at 6 months, associated with greater WFLP at 12 months. Strong genetic factors were not identified.

Gene-Centric Analysis of Preeclampsia Identifies Maternal Association at PLEKHG1Novelty and Significance

The genetic susceptibility to preeclampsia, a pregnancy-specific complication with significant maternal and fetal morbidity, has been poorly characterized. To identify maternal genes associated with preeclampsia risk, we assembled 498 cases and 1864 controls of European ancestry from preeclampsia case-control collections in 5 different US sites (with additional matched population controls), genotyped samples on a cardiovascular gene-centric array composed of variants from ≈2000 genes selected based on prior genetic studies of cardiovascular and metabolic diseases and performed case-control genetic association analysis on 27 429 variants passing quality control. In silico replication testing of 9 lead signals with P<10−4 was performed in independent European samples from the SOPHIA (Study of Pregnancy Hypertension in Iowa) and Inova cohorts (212 cases, 456 controls). Multiethnic assessment of lead signals was then performed in samples of black (26 cases, 136 controls), Hispanic (132 cases, 468 controls), and East Asian (9 cases, 80 controls) ancestry. Multiethnic meta-analysis (877 cases, 3004 controls) revealed a study-wide statistically significant association of the rs9478812 variant in the pleiotropic PLEKHG1 gene (odds ratio, 1.40 [1.23–1.60]; Pmeta=5.90×10−7). The rs9478812 effect was even stronger in the subset of European cases with known early-onset preeclampsia (236 cases diagnosed <37 weeks, 1864 controls; odds ratio, 1.59 [1.27–1.98]; P=4.01×10−5). PLEKHG1 variants have previously been implicated in genome-wide association studies of blood pressure, body weight, and neurological disorders. Although larger studies are required to further define maternal preeclampsia heritability, this study identifies a novel maternal risk locus for further investigation.

Comparison of Infant Gut and Skin Microbiota, Resistome and Virulome Between Neonatal Intensive Care Unit (NICU) Environments

Background: There is a growing move to provide care for premature infants in a single family, private room neonatal intensive care unit (NICU) in place of the traditional shared space, open bay NICU. The resultant effect on the developing neonatal microbiota is unknown. Study Design: Stool and groin skin swabs were collected from infants in a shared-space NICU (old NICU) and a single-family room NICU (new NICU) on the same hospital campus. Metagenomic sequencing was performed and data analyzed by CosmosID bioinformatics software package. Results: There were no significant differences between the cohorts in gestational age, length of stay, and delivery mode; infants in the old NICU received significantly more antibiotics (p = 0.03). Differentially abundant antimicrobial resistance genes and virulence associated genes were found between the cohorts in stool and skin, with more differentially abundant antimicrobial resistance genes in the new NICU. The entire bacterial microbiota analyzed to the genus level significantly differed between cohorts in skin (p = 0.0001) but not in stool samples. There was no difference in alpha diversity between the two cohorts. DNA viruses and fungi were detected but did not differ between cohorts. Conclusion: Differences were seen in the resistome and virulome between the two cohorts with more differentially abundant antimicrobial resistance genes in the new NICU. This highlights the influence that different NICU environments can have on the neonatal microbiota. Whether the differences were due to the new NICU being a single-family NICU or located in a newly constructed building warrants exploration. Long term health outcomes from the differences observed must be followed longitudinally.

Abstract IA18: Large-scale familial whole genome sequencing to evaluate genetic risk.

Abstract Whole genome sequencing (WGS) technology and analysis is quickly approaching the stage of development where it can become a medically recognized procedure for prognostics as well as diagnostics. Critical to the development of medical-grade whole genome sequencing is the ability to recognize and minimize technological and biological variation in WGS data. The Inova Translational Medicine Institute (ITMI) has completed a study that generated 1500 whole genome sequences in 15 months and recently launched a study that will generate 20,000 WGS over the next two years. The 1500 sequenced genomes were from individuals from 53 countries, representing four major ancestral groups and many minor sub-groups. ITMI used these data to generate a database of ancestral-specific variants. This database can be used to identify single nucleotide variants in patients with a specific ancestral background as ancestral-specific sequences instead of mutations. This ancestral information was applied to the 487 cancer genes identified in the Wellcome Trust Sanger Institutes Cancer Gene Census, in an attempt to identify germline mutations in these genes, in our cohort of 1500 participants. The result of this analysis identifies the incidence and type of germline mutations in various ethnic groups. The ethical question that remains is what to do with incidental finding of this type as medical whole genome sequencing becomes a common tool in the practice of medicine. Citation Format: Joseph Vockley, Ramaswamy Iyer, Kathi Huddleston, John Niederhuber. Large-scale familial whole genome sequencing to evaluate genetic risk. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA18.