An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

Novel genetic loci associated with hippocampal volume

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five novel loci for intracranial volume and confirmed two known signals. Four of the loci are also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic=0.748), which indicated a similar genetic background and allowed for the identification of four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, Parkinson’s disease, and enriched near genes involved in growth pathways including PI3K–AKT signaling. These findings identify biological underpinnings of intracranial volume and provide genetic support for theories on brain reserve and brain overgrowth

Genetic architecture of subcortical brain structures in 38,851 individuals

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease

Genetic architecture of subcortical brain structures in 38,851 individuals

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Saccharomyces cerevisiae CEN.PK113-7D: Anaerobically evolved fungi that harbor Class II dihydroorotate dehydrogenase enzymes that function independently of the respiratory chain

The goal of this study was elucidate the respiratory chain dependency of the abovementioned Class II DHODs. The URA9 genes of Anaeromyces robustus, Sch. japonicus, D. bruxellensis, O. parapolymorpha and K. marxianus were expressed in a ura1 null mutant of S. cerevisiae and growth was studied under anaerobic conditions. The subcellular localization of the enzymes was determined by fluorescence microscopy of GFP-fused Ura9 proteins. Finally, alternative electron acceptors were determined for these proteins by enzyme assays using cell free extracts and mitochondrial extracts of S. cerevisiae ura1 null mutants expressing the URA9 genes from a multicopy plasmid

Saccharomyces cerevisiae CEN.PK113-7D: Anaerobically evolved fungi that harbor Class II dihydroorotate dehydrogenase enzymes that function independently of the respiratory chain

The goal of this study was elucidate the respiratory chain dependency of the abovementioned Class II DHODs. The URA9 genes of Anaeromyces robustus, Sch. japonicus, D. bruxellensis, O. parapolymorpha and K. marxianus were expressed in a ura1 null mutant of S. cerevisiae and growth was studied under anaerobic conditions. The subcellular localization of the enzymes was determined by fluorescence microscopy of GFP-fused Ura9 proteins. Finally, alternative electron acceptors were determined for these proteins by enzyme assays using cell free extracts and mitochondrial extracts of S. cerevisiae ura1 null mutants expressing the URA9 genes from a multicopy plasmid

Class-II dihydroorotate dehydrogenases from three phylogenetically distant fungi support anaerobic pyrimidine biosynthesis

Abstract Background In most fungi, quinone-dependent Class-II dihydroorotate dehydrogenases (DHODs) are essential for pyrimidine biosynthesis. Coupling of these Class-II DHODHs to mitochondrial respiration makes their in vivo activity dependent on oxygen availability. Saccharomyces cerevisiae and closely related yeast species harbor a cytosolic Class-I DHOD (Ura1) that uses fumarate as electron acceptor and thereby enables anaerobic pyrimidine synthesis. Here, we investigate DHODs from three fungi (the Neocallimastigomycete Anaeromyces robustus and the yeasts Schizosaccharomyces japonicus and Dekkera bruxellensis) that can grow anaerobically but, based on genome analysis, only harbor a Class-II DHOD. Results Heterologous expression of putative Class-II DHOD-encoding genes from fungi capable of anaerobic, pyrimidine-prototrophic growth (Arura9, SjURA9, DbURA9) in an S. cerevisiae ura1Δ strain supported aerobic as well as anaerobic pyrimidine prototrophy. A strain expressing DbURA9 showed delayed anaerobic growth without pyrimidine supplementation. Adapted faster growing DbURA9-expressing strains showed mutations in FUM1, which encodes fumarase. GFP-tagged SjUra9 and DbUra9 were localized to S. cerevisiae mitochondria, while ArUra9, whose sequence lacked a mitochondrial targeting sequence, was localized to the yeast cytosol. Experiments with cell extracts showed that ArUra9 used free FAD and FMN as electron acceptors. Expression of SjURA9 in S. cerevisiae reproducibly led to loss of respiratory competence and mitochondrial DNA. A cysteine residue (C265 in SjUra9) in the active sites of all three anaerobically active Ura9 orthologs was shown to be essential for anaerobic activity of SjUra9 but not of ArUra9. Conclusions Activity of fungal Class-II DHODs was long thought to be dependent on an active respiratory chain, which in most fungi requires the presence of oxygen. By heterologous expression experiments in S. cerevisiae, this study shows that phylogenetically distant fungi independently evolved Class-II dihydroorotate dehydrogenases that enable anaerobic pyrimidine biosynthesis. Further structure–function studies are required to understand the mechanistic basis for the anaerobic activity of Class-II DHODs and an observed loss of respiratory competence in S. cerevisiae strains expressing an anaerobically active DHOD from Sch. japonicus