Genomic study of TEX15 variants: prevalence and allelic heterogeneity in men with spermatogenic failure.

Introduction: Human spermatogenesis is a highly intricate process that requires the input of thousands of testis-specific genes. Defects in any of them at any stage of the process can have detrimental effects on sperm production and/or viability. In particular, the function of many meiotic proteins encoded by germ cell specific genes is critical for maturation of haploid spermatids and viable spermatozoa, necessary for fertilization, and is also extremely sensitive to even the slightest change in coding DNA. Methods: Here, using whole exome and genome approaches, we identified and reported novel, clinically significant variants in testis-expressed gene 15 (TEX15), in unrelated men with spermatogenic failure (SPGF). Results: TEX15 mediates double strand break repair during meiosis. Recessive loss-of-function (LOF) TEX15 mutations are associated with SPGF in humans and knockout male mice are infertile. We expand earlier reports documenting heterogeneous allelic pathogenic TEX15 variants that cause a range of SPGF phenotypes from oligozoospermia (low sperm) to nonobstructive azoospermia (no sperm) with meiotic arrest and report the prevalence of 0.6% of TEX15 variants in our patient cohort. Among identified possible LOF variants, one homozygous missense substitution c.6835G>A (p.Ala2279Thr) co-segregated with cryptozoospermia in a family with SPGF. Additionally, we observed numerous cases of inferred in trans compound heterozygous variants in TEX15 among unrelated individuals with varying degrees of SPGF. Variants included splice site, insertions/deletions (indels), and missense substitutions, many of which resulted in LOF effects (i.e., frameshift, premature stop, alternative splicing, or potentially altered posttranslational modification sites). Conclusion: In conclusion, we performed an extensive genomic study of familial and sporadic SPGF and identified potentially damaging TEX15 variants in 7 of 1097 individuals of our combined cohorts. We hypothesize that SPGF phenotype severity is dictated by individual TEX15 variant's impact on structure and function. Resultant LOFs likely have deleterious effects on crossover/recombination in meiosis. Our findings support the notion of increased gene variant frequency in SPGF and its genetic and allelic heterogeneity as it relates to complex disease such as male infertility.

Variants in GCNA, X-linked germ-cell genome integrity gene, identified in men with primary spermatogenic failure.

Male infertility impacts millions of couples yet, the etiology of primary infertility remains largely unknown. A critical element of successful spermatogenesis is maintenance of genome integrity. Here, we present a genomic study of spermatogenic failure (SPGF). Our initial analysis (n = 176) did not reveal known gene-candidates but identified a potentially significant single-nucleotide variant (SNV) in X-linked germ-cell nuclear antigen (GCNA). Together with a larger follow-up study (n = 2049), 7 likely clinically relevant GCNA variants were identified. GCNA is critical for genome integrity in male meiosis and knockout models exhibit impaired spermatogenesis and infertility. Single-cell RNA-seq and immunohistochemistry confirm human GCNA expression from spermatogonia to elongated spermatids. Five identified SNVs were located in key functional regions, including N-terminal SUMO-interacting motif and C-terminal Spartan-like protease domain. Notably, variant p.Ala115ProfsTer7 results in an early frameshift, while Spartan-like domain missense variants p.Ser659Trp and p.Arg664Cys change conserved residues, likely affecting 3D structure. For variants within GCNA's intrinsically disordered region, we performed computational modeling for consensus motifs. Two SNVs were predicted to impact the structure of these consensus motifs. All identified variants have an extremely low minor allele frequency in the general population and 6 of 7 were not detected in > 5000 biological fathers. Considering evidence from animal models, germ-cell-specific expression, 3D modeling, and computational predictions for SNVs, we propose that identified GCNA variants disrupt structure and function of the respective protein domains, ultimately arresting germ-cell division. To our knowledge, this is the first study implicating GCNA, a key genome integrity factor, in human male infertility.

Assessing the accuracy of blood RNA profiles to identify patients with post-concussion syndrome: A pilot study in a military patient population.

Mild traumatic brain injury (mTBI) is a complex, neurophysiological condition that can have detrimental outcomes. Yet, to date, no objective method of diagnosis exists. Physical damage to the blood-brain-barrier and normal waste clearance via the lymphatic system may enable the detection of biomarkers of mTBI in peripheral circulation. Here we evaluate the accuracy of whole transcriptome analysis of blood to predict the clinical diagnosis of post-concussion syndrome (PCS) in a military cohort. Sixty patients with clinically diagnosed chronic concussion and controls (no history of concussion) were recruited (retrospective study design). Male patients (46) were split into a training set comprised of 20 long-term concussed (> 6 months and symptomatic) and 12 controls (no documented history of concussion). Models were validated in a testing set (control = 9, concussed = 5). RNA_Seq libraries were prepared from whole blood samples for sequencing using a SOLiD5500XL sequencer and aligned to hg19 reference genome. Patterns of differential exon expression were used for diagnostic modeling using support vector machine classification, and then validated in a second patient cohort. The accuracy of RNA profiles to predict the clinical diagnosis of post-concussion syndrome patients from controls was 86% (sensitivity 80%; specificity 89%). In addition, RNA profiles reveal duration of concussion. This pilot study shows the potential utility of whole transcriptome analysis to establish the clinical diagnosis of chronic concussion syndrome.

Blood transcriptome changes after stroke in an African American population.

OBJECTIVE: Molecular diagnostic medicine holds much promise to change point of care treatment. An area where additional diagnostic tools are needed is in acute stroke care, to assist in diagnosis and prognosis. Previous studies using microarray-based gene expression analysis of peripheral blood following stroke suggests this approach may be effective. Next-generation sequencing (NGS) approaches have expanded genomic analysis and are not limited to previously identified genes on a microarray chip. Here, we report on a pilot NGS study to identify gene expression and exon expression patterns for the prediction of stroke diagnosis and prognosis. METHODS: We recruited 28 stroke patients and 28 age- and sex-matched hypertensive controls. RNA was extracted from 3 mL blood samples, and RNA-Seq libraries were assembled and sequenced. RESULTS: Bioinformatical analysis of the aligned RNA data reveal exonic (30%), intronic (36%), and novel RNA components (not currently annotated: 33%). We focused our study on patients with confirmed middle cerebral artery occlusion ischemic stroke (n = 17). On the basis of our observation of differential splicing of gene transcripts, we used all exonic RNA expression rather than gene expression (combined exons) to build prediction models using support vector machine algorithms. Based on model building, these models have a high predicted accuracy rate >90% (spec. 88% sen. 92%). We further stratified outcome based on the improvement in NIHss scores at discharge; based on model building we observe a predicted 100% accuracy rate. INTERPRETATION: NGS-based exon expression analysis approaches have a high potential for patient diagnosis and outcome prediction, with clear utility to aid in clinical patient care.