Viatcheslav R. Akmaev

Pan-ethnic carrier screening and prenatal diagnosis for spinal muscular atrophy: clinical laboratory analysis of >72 400 specimens

Spinal muscular atrophy (SMA) is a leading inherited cause of infant death with a reported incidence of ∼1 in 10 000 live births and is second to cystic fibrosis as a common, life-shortening autosomal recessive disorder. The American College of Medical Genetics has recommended population carrier screening for SMA, regardless of race or ethnicity, to facilitate informed reproductive options, although other organizations have cited the need for additional large-scale studies before widespread implementation. We report our data from carrier testing (n=72 453) and prenatal diagnosis (n=121) for this condition. Our analysis of large-scale population carrier screening data (n=68 471) demonstrates the technical feasibility of high throughput testing and provides mutation carrier and allele frequencies at a level of accuracy afforded by large data sets. In our United States pan-ethnic population, the calculated a priori carrier frequency of SMA is 1/54 with a detection rate of 91.2%, and the pan-ethnic disease incidence is calculated to be 1/11 000. Carrier frequency and detection rates provided for six major ethnic groups in the United States range from 1/47 and 94.8% in the Caucasian population to 1/72 and 70.5% in the African American population, respectively. This collective experience can be utilized to facilitate accurate pre- and post-test counseling in the settings of carrier screening and prenatal diagnosis for SMA.

Vascular Gene Expression in Nonneoplastic and Malignant Brain

Malignant gliomas are uniformly lethal tumors whose morbidity is mediated in large part by the angiogenic response of the brain to the invading tumor. This profound angiogenic response leads to aggressive tumor invasion and destruction of surrounding brain tissue as well as blood-brain barrier breakdown and life-threatening cerebral edema. To investigate the molecular mechanisms governing the proliferation of abnormal microvasculature in malignant brain tumor patients, we have undertaken a cell-specific transcriptome analysis from surgically harvested nonneoplastic and tumor-associated endothelial cells. SAGE-derived endothelial cell gene expression patterns from glioma and nonneoplastic brain tissue reveal distinct gene expression patterns and consistent up-regulation of certain glioma endothelial marker genes across patient samples. We define the G-protein-coupled receptor RDC1 as a tumor endothelial marker whose expression is distinctly induced in tumor endothelial cells of both brain and peripheral vasculature. Further, we demonstrate that the glioma-induced gene, PV1, shows expression both restricted to endothelial cells and coincident with endothelial cell tube formation. As PV1 provides a framework for endothelial cell caveolar diaphragms, this protein may serve to enhance glioma-induced disruption of the blood-brain barrier and transendothelial exchange. Additional characterization of this extensive brain endothelial cell gene expression database will provide unique molecular insights into vascular gene expression.

Differences in SMN1 allele frequencies among ethnic groups within North America

Background: Spinal muscular atrophy (SMA) is the most common inherited lethal disease of children. Various genetic deletions involving the bi-allelic loss of SMN1 exon 7 are reported to account for 94% of affected individuals. Published literature places the carrier frequency for SMN1 mutations between 1 in 25 and 1 in 50 in the general population. Although SMA is considered to be a pan-ethnic disease, carrier frequencies for many ethnicities, including most ethnic groups in North America, are unknown. Objectives and methods: To provide an accurate assessment of SMN1 mutation carrier frequencies in African American, Ashkenazi Jewish, Asian, Caucasian, and Hispanic populations, more than 1000 specimens in each ethnic group were tested using a clinically validated, quantitative real-time polymerase chain reaction (PCR) assay that measures exon 7 copy number. Results: The observed one-copy genotype frequency was 1 in 37 (2.7%) in Caucasian, 1 in 46 (2.2%) in Ashkenazi Jew, 1 in 56 (1.8%) in Asian, 1 in 91 (1.1%) in African American, and 1 in 125 (0.8%) in Hispanic specimens. Additionally, an unusually high frequency of alleles with multiple copies of SMN1 was identified in the African American group (27% compared to 3.3–8.1%). This latter finding has clinical implications for providing accurate adjusted genetic risk assessments to the African American population. Conclusions: Differences in the frequency of SMA carriers were significant among several ethnic groups. This study provides an accurate assessment of allele frequencies and estimates of adjusted genetic risk that were previously unavailable to clinicians and patients considering testing.

Genetic heterozygosity and pseudodeficiency in the Pompe disease newborn screening pilot program

Pompe disease is an autosomal recessive lysosomal storage disorder (LSD) caused by deficiency of lysosomal acid alpha-glucosidase (GAA) activity. This is the first LSD in which newborn screening has been shown to improve clinical outcomes. Newborn screening also identified multiple rare gene variants in this population. Among 132,538 newborns screened, 107 babies (1 in 1239) who had low dried blood spot GAA activity were genotyped. Sixty-nine (64.5%) babies had a total of 54 mutations and 35 novel predictably pathogenic mutations; 36 babies (33.6%) who had no mutation were homozygous for the c.[1726A; 2065A] pseudodeficiency allele. Because 81% of the chromosomes (14% in the controls) were in haplotype *03, we found a link between the pseudodeficiency allele and other mutated alleles. The newborns with Pompe disease detected by screening had lymphocyte GAA activities 0.45 to 1.65 nmol/mg/h (normal 66.7+/-33.8), while only 2 of the 100 false-positive cases had GAA activity less than 2.00 nmol/mg/h (or 3% of the normal mean). Therefore, newborn screening for Pompe disease could be successfully conducted by including genotyping and lymphocyte GAA assay, even in a population with mutation heterozygosity and pseudodeficiency.

The human sex ratio from conception to birth

Significance The human sex ratio has long interested cell biologists, developmental biologists, demographers, epidemiologists, evolutionary biologists, gynecologists, and statisticians. Nonetheless, the trajectory of the human sex ratio from conception to birth has been poorly characterized. We present the most comprehensive analysis of this trajectory ever done. Our dataset is the largest ever assembled to estimate the sex ratio at conception and is the first, to our knowledge, to include data from 3- to- 6-d-old embryos, induced abortions, chorionic villus sampling, amniocentesis, and fetal deaths and live births. Our results indicate that the sex ratio at conception is unbiased, the proportion of males increases during the first trimester, and total female mortality during pregnancy exceeds total male mortality; these are fundamental insights into early human development. We describe the trajectory of the human sex ratio from conception to birth by analyzing data from (i) 3- to 6-d-old embryos, (ii) induced abortions, (iii) chorionic villus sampling, (iv) amniocentesis, and (v) fetal deaths and live births. Our dataset is the most comprehensive and largest ever assembled to estimate the sex ratio at conception and the sex ratio trajectory and is the first, to our knowledge, to include all of these types of data. Our estimate of the sex ratio at conception is 0.5 (proportion male), which contradicts the common claim that the sex ratio at conception is male-biased. The sex ratio among abnormal embryos is male-biased, and the sex ratio among normal embryos is female-biased. These biases are associated with the abnormal/normal state of the sex chromosomes and of chromosomes 15 and 17. The sex ratio may decrease in the first week or so after conception (due to excess male mortality); it then increases for at least 10–15 wk (due to excess female mortality), levels off after ∼20 wk, and declines slowly from 28 to 35 wk (due to excess male mortality). Total female mortality during pregnancy exceeds total male mortality. The unbiased sex ratio at conception, the increase in the sex ratio during the first trimester, and total mortality during pregnancy being greater for females are fundamental insights into early human development.

Correction of sequence-based artifacts in serial analysis of gene expression

MOTIVATION Serial Analysis of Gene Expression (SAGE) is a powerful technology for measuring global gene expression, through rapid generation of large numbers of transcript tags. Beyond their intrinsic value in differential gene expression analysis, SAGE tag collections afford abundant information on the size and shape of the sample transcriptome and can accelerate novel gene discovery. These latter SAGE applications are facilitated by the enhanced method of Long SAGE. A characteristic of sequencing-based methods, such as SAGE and Long SAGE is the unavoidable occurrence of artifact sequences resulting from sequencing errors. By virtue of their low-random incidence, such tag errors have minimal impact on differential expression analysis. However, to fully exploit the value of large SAGE tag datasets, it is desirable to account for and correct tag artifacts. RESULTS We present estimates for occurrences of tag errors, and an efficient error correction algorithm. Error rate estimates are based on a stochastic model that includes the Polymerase chain reaction and sequencing error contributions. The correction algorithm, SAGEScreen, is a multi-step procedure that addresses ditag processing, estimation of empirical error rates from highly abundant tags, grouping of similar-sequence tags and statistical testing of observed counts. We apply SAGEScreen to Long SAGE libraries and compare error rates for several processing scenarios. Results with simulated tag collections indicate that SAGEScreen corrects 78% of recoverable tag errors and reduces the occurrences of singleton tags. AVAILABILITY The SAGEScreen software is available for academic users from the first author.

Cystic Fibrosis Carrier Testing in an Ethnically Diverse US Population

BACKGROUND The incidence of cystic fibrosis (CF) and the frequency of specific disease-causing mutations vary among populations. Affected individuals experience a range of serious clinical consequences, notably lung and pancreatic disease, which are only partially dependent on genotype. METHODS An allele-specific primer-extension reaction, liquid-phase hybridization to a bead array, and subsequent fluorescence detection were used in testing for carriers of 98 CFTR [cystic fibrosis transmembrane conductance regulator (ATP-binding cassette sub-family C, member 7)] mutations among 364 890 referred individuals with no family history of CF. RESULTS One in 38 individuals carried one of the 98 CFTR mutations included in this panel. Of the 87 different mutations detected, 18 were limited to a single ethnic group. African American, Hispanic, and Asian individuals accounted for 33% of the individuals tested. The mutation frequency distribution of Caucasians was significantly different from that of each of these ethnic groups (P < 1 × 10⁻¹⁰). CONCLUSIONS Carrier testing using a broad mutation panel detects differences in the distribution of mutations among ethnic groups in the US.

A GC-Wave Correction Algorithm that Improves the Analytical Performance of aCGH

Array-based comparative genome hybridization (aCGH) is a powerful, data-intensive technique used to identify genomic copy number variation throughout the human genome. The use of aCGH clinically to identify pathogenic copy number aberrations is becoming common, and the statistical and mathematical algorithms used in aCGH data analysis play an important role in determining the performance of these platforms. Interpretation of aCGH data can be complicated by a platform-independent technical artifact described as GC-waves, which are wave patterns in CGH data correlating to regional GC-content of the human genome that can reduce the clinical specificity and sensitivity of aCGH platforms. We describe an automated GC-wave correction algorithm and techniques to understand how the correction affects the analytical performance of aCGH. This GC-correction algorithm was effective at mitigating GC-wave effects. After correction, array data were measurably improved by the algorithm, demonstrating improvements in specificity and sensitivity and in overall data quality.

Correction of technology-related artifacts in serial analysis of gene expression.

Serial analysis of gene expression (SAGE) is a powerful technique for measuring global gene expression through sampling of transcript tags. SAGE tag collections or libraries serve as a rich data source for differential gene expression analysis, transcriptome mapping, and gene discovery. Transcriptome mapping and gene discovery are facilitated by extensions of SAGE, e.g., Long SAGE, where the transcript tags are elongated by utilization of a different tagging enzyme. SAGE, as a sequencing-based technique, is prone to errors resulting in artifact SAGE tag sequences and erroneous tag numbers. A methodology to pinpoint and correct tag artifacts is necessary to fully exploit the value of large SAGE libraries. SAGEScreen is a tag sequence correction algorithm. The algorithm is a multistep procedure that addresses error rates and performs ditag and tag processing. The error rate estimates are based on a stochastic model of PCR and sequencing related mutations. The ditag processing step is essential for calculation of unbiased tag numbers, and the tag processing step allows for filtration of tag sequence artifacts and adjustment of tag numbers.