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bioRxiv2017

The Stratification Of Major Depressive Disorder Into Genetic Subgroups

Depression is a common and clinically heterogeneous mental health disorder that is frequently comorbid with other diseases and conditions. Stratification of depression may align sub-diagnoses more closely with their underling aetiology and provide more tractable targets for research and effective treatment. In the current study, we investigated whether genetic data could be used to identify subgroups within people with depression using the UK Biobank. Examination of cross-locus correlations was used to test for evidence of subgroups by examining whether there was clustering of independent genetic variants associated with eleven other complex traits and disorders in people with depression. We found evidence of a subgroup within depression using age of natural menopause variants (P = 1.69 x 10-3) and this effect remained significant in females (P = 1.18 x 10-3), but not males (P = 0.186). However, no evidence for this subgroup (P > 0.05) was found in Generation Scotland, iPSYCH, a UK Biobank replication cohort or the GERA cohort. In the UK Biobank, having depression was also associated with a later age of menopause (beta = 0.34, standard error = 0.06, P = 9.92 x 10-8). A potential age of natural menopause subgroup within depression and the association between depression and a later age of menopause suggests that they partially share a developmental pathway.

genetics↗

bioRxiv2017

Genome-Wide Association Study Reveals Genetic Link Between Diarrhea-Associated Entamoeba histolytica Infection And Inflammatory Bowel Disease

Diarrhea is the second leading cause of death for children globally, causing 760,000 deaths each year in children under the age of 5. Amoebic dysentery contributes significantly to this burden, especially in developing countries. We hypothesize that genetic variation contributes to susceptibility to diarrhea-associated Entamoeba histolytica infection in Bangladeshi infants; thus, we conducted a genome-wide association study (GWAS) in two independent birth cohorts of diarrhea-associated E. histolytica infection. Cases were defined as children with at least one diarrheal episode positive for E. histolytica through either PCR or ELISA within the first year of life. Controls were children without any episodes positive for E. histolytica in the same time frame. Meta-analyses under a fixed-effects inverse variance weighting model identified variants in two neighboring genes on chromosome 10: CUL2 (cullin 2) and CREM (cAMP responsive element modulator) associated with E. histolytica infection, with SNP rs58000832 achieving genome-wide significance (Pmeta=4.2x10-10). Each additional risk allele (an intergenic insertion between CREM and CCNY) of rs58000832 conferred 2.5 increased odds of a diarrhea-associated E. histolytica infection. The most associated SNP within a gene was in an intron of CREM (rs58468685, Pmeta=2.3x10-9), which with CUL2, has been implicated as a susceptibility locus for Inflammatory Bowel Disease (IBD) and Crohns Disease. Gene expression resources suggest these loci are related to the higher expression of CREM, but not CUL2. Increased CREM expression is also observed in early E. histolytica infection. Further, CREM-/- mice were more susceptible to E. histolytica amebic colitis. These genetic associations reinforce the pathological similarities observed in gut inflammation between E. histolytica infection and IBD.

genetics↗

bioRxiv2017

The iPSYCH2012 case-cohort sample: New directions for unravelling genetic and environmental architectures of severe mental disorders

The iPSYCH consortium has established a large Danish population-based Case-Cohort sample (iPSYCH2012) aimed at unravelling the genetic and environmental architecture of severe mental disorders. The iPSYCH2012 sample is nested within the entire Danish population born 1981-2005 including 1,472,762 persons. This paper introduces the iPSYCH2012 sample and outlines key future research directions. Cases were identified as persons with schizophrenia (N=3,540), autism (N=16,146), ADHD (N=18,726), and affective disorder (N=26,380), of which 1928 had bipolar affective disorder. Controls were randomly sampled individuals (N=30,000). Within the sample of 86,189 individuals, a total of 57,377 individuals had at least one major mental disorder. DNA was extracted from the neonatal dried blood spot samples obtained from the Danish Neonatal Screening Biobank and genotyped using the Illumina PsychChip. Genotyping was successful for 90% of the sample. The assessments of exome sequencing, methylation profiling, metabolome profiling, vitamin-D, inflammatory and neurotrophic factors are in progress. For each individual, the iPSYCH2012 sample also includes longitudinal information on health, prescribed medicine, social and socioeconomic information and analogous information among relatives. To the best of our knowledge, the iPSYCH2012 sample is the largest and most comprehensive data source for the combined study of genetic and environmental aetiologies of severe mental disorders.

genetics↗

bioRxiv2017

Comprehensive genome and transcriptome analysis reveals genetic basis for gene fusions in cancer

Gene fusions are an important class of cancer-driving events with therapeutic and diagnostic values, yet their underlying genetic mechanisms have not been systematically characterized. Here by combining RNA and whole genome DNA sequencing data from 1188 donors across 27 cancer types we obtained a list of 3297 high-confidence tumour-specific gene fusions, 82% of which had structural variant (SV) support and 2372 of which were novel. Such a large collection of RNA and DNA alterations provides the first opportunity to systematically classify the gene fusions at a mechanistic level. While many could be explained by single SVs, numerous fusions involved series of structural rearrangements and thus are composite fusions. We discovered 75 fusions of a novel class of inter-chromosomal composite fusions, termed bridged fusions, in which a third genomic location bridged two different genes. In addition, we identified 522 fusions involving non-coding genes and 157 ORF-retaining fusions, in which the complete open reading frame of one gene was fused to the UTR region of another. Although only a small proportion (5%) of the discovered fusions were recurrent, we found a set of highly recurrent fusion partner genes, which exhibited strong 5 or 3 bias and were significantly enriched for cancer genes. Our findings broaden the view of the gene fusion landscape and reveal the general properties of genetic alterations underlying gene fusions for the first time.

genetics↗

bioRxiv2017

Genome-wide analysis reveals distinct genetic mechanisms of diet-dependent lifespan and healthspan in D. melanogaster

Dietary restriction (DR) robustly extends lifespan and delays age-related diseases across species. An underlying assumption in aging research has been that DR mimetics extend both lifespan and healthspan jointly, though this has not been rigorously tested in different genetic backgrounds. Furthermore, nutrient response genes important for lifespan or healthspan extension remain underexplored, especially in natural populations. To address these gaps, we utilized over 150 DGRP strains to measure nutrient-dependent changes in lifespan and age-related climbing ability to measure healthspan. DR extended lifespan and delayed decline in climbing ability on average, but there was no evidence of correlation between these traits across individual strains. Through GWAS, we then identified and validated jughead and Ferredoxin as determinants of diet-dependent lifespan, and Daedalus for diet-dependent physical activity. Modulating these genes produced independent effects on lifespan and climbing ability, further suggesting that these age-related traits are likely to be regulated through distinct genetic mechanisms.

genetics↗

bioRxiv2017

A genetic investigation of sex bias in the prevalence of attention deficit hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) shows substantial heritability and is 2-7 times more common in males than females. We examined two putative genetic mechanisms underlying this sex bias: sex-specific heterogeneity and higher burden of risk in female cases. We analyzed genome-wide common variants from the Psychiatric Genomics Consortium and iPSYCH Project (20,183 cases, 35,191 controls) and Swedish population-registry data (N=77,905 cases, N=1,874,637 population controls). We find strong genetic correlation for ADHD across sex and no mean difference in polygenic burden across sex. In contrast, siblings of female probands are at an increased risk of ADHD, compared to siblings of male probands. The results also suggest that females with ADHD are at especially high risk of comorbid developmental conditions. Overall, this study supports a greater familial burden of risk in females with ADHD and some clinical and etiological heterogeneity. However, autosomal common variants largely do not explain the sex bias in ADHD prevalence.

genetics↗

bioRxiv2017

Psychosis and the level of mood incongruence in Bipolar Disorder are related to genetic liability for Schizophrenia

ImportanceBipolar disorder (BD) overlaps schizophrenia in its clinical presentation and genetic liability. Alternative approaches to patient stratification beyond current diagnostic categories are needed to understand the underlying disease processes/mechanisms.\n\nObjectivesTo investigate the relationship between common-variant liability for schizophrenia, indexed by polygenic risk scores (PRS) and psychotic presentations of BD, using clinical descriptions which consider both occurrence and level of mood-incongruent psychotic features.\n\nDesignCase-control design: using multinomial logistic regression, to estimate differential associations of PRS across categories of cases and controls.\n\nSettings & Participants4399 BDcases, mean [sd] age-at-interview 46[12] years, of which 2966 were woman (67%) from the BD Research Network (BDRN) were included in the final analyses, with data for 4976 schizophrenia cases and 9012 controls from the Type-1 diabetes genetics consortium and Generation Scotland included for comparison.\n\nExposureStandardised PRS, calculated using alleles with an association p-value threshold < 0.05 in the second Psychiatric Genomics Consortium genome-wide association study of schizophrenia, adjusted for the first 10 population principal components and genotyping-platform.\n\nMain outcome measureMultinomial logit models estimated PRS associations with BD stratified by (1) Research Diagnostic Criteria (RDC) BD subtypes (2) Lifetime occurrence of psychosis.(3) Lifetime mood-incongruent psychotic features and (4) ordinal logistic regression examined PRS associations across levels of mood-incongruence. Ratings were derived from the Schedule for Clinical Assessment in Neuropsychiatry interview (SCAN) and the Bipolar Affective Disorder Dimension Scale (BADDS).\n\nResultsAcross clinical phenotypes, there was an exposure-response gradient with the strongest PRS association for schizophrenia (RR=1.94, (95% C.1.1.86, 2.01)), then schizoaffective BD (RR=1.37, (95% C.I. 1.22, 1.54)), BD I (RR= 1.30, (95% C.I. 1.24, 1.36)) and BD II (RR=1.04, (95% C.1. 0.97, 1.11)). Within BD cases, there was an effect gradient, indexed by the nature of psychosis, with prominent mood-incongruent psychotic features having the strongest association (RR=1.46, (95% C.1.1.36, 1.57)), followed by mood-congruent psychosis (RR= 1.24, (95% C.1. 1.17, 1.33)) and lastly, BD cases with no history of psychosis (RR= 1.09, (95% C.1. 1.04, 1.15)).\n\nConclusionWe show for the first time a polygenic-risk gradient, across schizophrenia and bipolar disorder, indexed by the occurrence and level of mood-incongruent psychotic symptoms.

genetics↗

bioRxiv2017

Forward Genetic ENU Mutagenesis Screen for Mouse Models of Chronic Fatigue Identifies a Novel Mutation in Slc2a4 (GLUT4)

In a screen of voluntary wheel-running behavior designed to identify genetic mouse models of chronic fatigue in ENU mutagenized C57BL/6J mice, we discovered two lines that showed aberrant wheel-running patterns. These lines both stem from a single original founder identified as a low body-weight candidate in a recessive screen. Progeny from both of these lines showed the abnormal wheel-running behavior, with affected mice showing significantly lower daily activity levels than unaffected mice. They also exhibited low amplitude circadian rhythms, consisting of lower activity levels during the normal active phase, and increased levels of activity during the rest or light phase, but only a modest alteration in free-running period. Their activity is not consolidated into longer bouts, but is frequently interrupted with periods of inactivity throughout the dark phase of the light-dark (LD) cycle. As seen with the low body weight, expression of the behavioral phenotypes in offspring of strategic crosses was consistent with a recessive heritance pattern. Mapping of these phenotypic abnormalities showed linkage to a single locus on chromosome 11, and whole exome sequencing (WES) identified a single point mutation in the Slc2a4 gene encoding the GLUT4 insulin-responsive glucose transporter. The single nucleotide change (A to T) was found in the distal end of exon 10, and results in a premature stop (Y440*). To our knowledge, this is the first time a mutation in this gene has been shown to result in extensive changes in general behavioral patterns.\n\nSIGNIFICANCE STATEMENTChronic fatigue is a debilitating and devastating disorder with widespread consequences for both the patient and the persons around them, but effective treatment strategies are lacking. The identification of novel genetic mouse models of chronic fatigue may prove invaluable for the study of its underlying physiological mechanisms and for the testing of treatments and interventions. A novel mutation in Slc2a4 (GLUT4) was identified in a forward mutagenesis screen because affected mice showed abnormal daily patterns and levels of wheel running consistent with chronic fatigue. This new mouse model may shed light on the pathophysiology of chronic fatigue.

genetics↗

bioRxiv2017

A genetic-based algorithm for recovery: A pilot study

Exercise training creates a number of physical challenges to the body, the overcoming of which drives exercise adaptation. The balance between sufficient stress and recovery is a crucial, but often under-explored, area within exercise training. Genetic variation can also predispose some individuals to a greater need for recovery after exercise. In this pilot study, 18 male soccer players underwent a repeated sprint training session. Countermovement jump (CMJ) heights were recorded immediately pre-and post-training, and at 24-and 48-hours post-training. The reduction in CMJ height was greatest at all post-training time points in subjects with a larger number of gene variants associated with a reduced exercise recovery. This suggests that knowledge of genetic information can be important in individualizing recovery timings and modalities in athletes following training.

genetics↗

bioRxiv2017

Genetics of vaccination-related narcolepsy

Narcolepsy type 1 is a severe hypersomnia affecting 1/3000 individuals. It is caused by a loss of neurons producing hypocretin/orexin in the hypothalamus. In 2009/2010, an immunization campaign directed towards the new pandemic H1N1 Influenza-A strain was launched and increased risk of narcolepsy reported in Northern European countries following vaccination with Pandemrix(R), an adjuvanted H1N1 vaccine resulting in ~250 vaccination-related cases in Finland alone. Using whole genome sequencing data of 2000 controls, exome sequencing data of 5000 controls and HumanCoreExome chip genotypes of 81 cases with vaccination-related narcolepsy and 2796 controls, we, built a multilocus genetic risk score with established narcolepsy risk variants. We also analyzed, whether novel risk variants would explain vaccine-related narcolepsy. We found that previously discovered risk variants had strong predictive power (accuracy of 73% and P<2.2*10-16; and ROC curve AUC 0.88) in vaccine-related narcolepsy cases with only 4.9% of cases being assigned to the low risk category. Our findings indicate genetic predisposition to vaccine-triggered narcolepsy, with the possibility of identifying 95% of people at risk.

genetics↗

bioRxiv2018

Long-read sequencing across the C9orf72 ‘GGGGCC’ repeat expansion: implications for genetic discovery efforts in human disease

Background: Many neurodegenerative diseases are caused by nucleotide repeat expansions, but most expansions, like the C9orf72 GGGGCC (G4C2) repeat that causes approximately 5-7% of all amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) cases, are too long to sequence using short-read sequencing technologies. It is unclear whether long-read sequencing technologies can traverse these long, challenging repeat expansions. Here, we demonstrate that two long-read sequencing technologies, Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), can sequence through disease-causing repeats cloned into plasmids, including the FTD/ALS-causing G4C2 repeat expansion. We also report the first long-read sequencing data characterizing the C9orf72 G4C2 repeat expansion at the nucleotide level in two symptomatic expansion carriers using PacBio whole-genome sequencing and a no-amplification (No-Amp) targeted approach based on CRISPR/Cas9.\n\nResults: Both the PacBio and ONT platforms successfully sequenced through the repeat expansions in plasmids. Throughput on the MinlON was a challenge for whole-genome sequencing; we were unable to attain reads covering the human C9orf72 repeat expansion using 15 flow cells. We obtained 8x coverage across the C9orf72 locus using the PacBio Sequel, accurately reporting the unexpanded allele at eight repeats, and reading through the entire expansion with 1324 repeats (7941 nucleotides). Using the No-Amp targeted approach, we attained >800x coverage and were able to identify the unexpanded allele, closely estimate expansion size, and assess nucleotide content in a single experiment. We estimate the individuals repeat region was >99% G4C2 content, though we cannot rule out small interruptions.\n\nConclusions: Our findings indicate that long-read sequencing is well suited to characterizing known repeat expansions, and for discovering new disease-causing, disease-modifying, or risk-modifying repeat expansions that have gone undetected with conventional short-read sequencing. The PacBio No-Amp targeted approach may have future potential in clinical and genetic counseling environments. Larger and deeper long-read sequencing studies in C9orf72 expansion carriers will be important to determine heterogeneity and whether the repeats are interrupted by non-G4C2 content, potentially mitigating or modifying disease course or age of onset, as interruptions are known to do in other repeat-expansion disorders. These results have broad implications across all diseases where the genetic etiology remains unclear.

genetics↗

bioRxiv2017

Fast and Powerful Genome Wide Association Analysis of Dense Genetic Data with High Dimensional Imaging Phenotypes

Genome wide association (GWA) analysis of brain imaging phenotypes can advance our understanding of the genetic basis of normal and disorder-related variation in the brain. GWA approaches typically use linear mixed effect models to account for non-independence amongst subjects due to factors such as family relatedness and population structure. The use of these models with high-dimensional imaging phenotypes presents enormous challenges in terms of computational intensity and the need to account multiple testing in both the imaging and genetic domain. Here we present method that makes mixed models practical with high-dimensional traits by a combination of a transformation applied to the data and model, and the use of a non-iterative variance component estimator. With such speed enhancements permutation tests are feasible, which allows inference on powerful spatial tests like the cluster size statistic.

genetics↗

bioRxiv2017

Genetic Analysis of Lodging in Diverse Maize Hybrids

Damage caused by lodging is a significant problem in corn production that results in estimated annual yield losses of 5-20%. Over the past 100 years, substantial maize breeding efforts have increased lodging resistance by artificial selection. However, less research has focused on understanding the genetic architecture underlying lodging. Lodging is a problematic trait to evaluate since it is greatly influenced by environmental factors such as wind, rain, and insect infestation, which make replication difficult. In this study over 1,723 diverse inbred maize genotypes were crossed to a common tester and evaluated in five environments over multiple years. Natural lodging due to severe weather conditions occurred in all five environments. By testing a large population of genetically diverse maize lines in multiple field environments, we detected significant correlations for this highly environmentally influenced trait across environments and with important agronomic traits such as yield and plant height. This study also permitted the mapping of quantitative trait loci (QTL) for lodging. Several QTL identified in this study overlapped with loci previously mapped for stalk strength in related maize inbred lines. QTL intervals mapped in this study also overlapped candidate genes implicated in the regulation of lignin and cellulose synthesis.

genetics↗

bioRxiv2017

Sodium valproate rescues expression of TRANK1 in iPSC-derived neural cells that carry a genetic variant associated with serious mental illness

Biological characterization of genetic variants identified in genome-wide association studies (GWAS) remains a substantial challenge. Here we used human induced pluripotent stem cells (hiPSC) and their neural derivatives to characterize common variants on chromosome 3p22 that have been associated by GWAS with major mental illnesses. HiPSC-derived neural progenitor cells carrying the risk allele of the single nucleotide polymorphism (SNP), rs9834970, displayed lower baseline TRANK1 expression that was rescued by chronic treatment with therapeutic dosages of valproic acid (VPA). Although rs9834970 has no known function, we demonstrated that a nearby SNP, rs90832, strongly affects binding by the transcription factor, CTCF, and that the high-affinity allele usually occurs on haplotypes carrying the rs9834970 risk allele. Decreased expression of TRANK1 perturbed expression of many genes involved in neural development and differentiation. These findings have important implications for the pathophysiology of major mental illnesses and the development of novel therapeutics.\n\nHighlightsO_LIhiPSC-derived neural cells carrying a mental illness risk allele showed lower expression of TRANK1\nC_LIO_LIValproic acid rescued TRANK1expression in cells carrying the risk allele\nC_LIO_LIRisk haplotypes usually carry an allele that increased CTCF binding\nC_LIO_LIReduced expression of TRANK1 perturbed genes involved in neural development and differentiation\nC_LI\n\nIn BriefUsing neural derivatives of human induced pluripotent stem cells, Jiang et al. demonstrate that genetic variants associated with mental illness alter transcription factor binding and decrease expression of a nearby gene, an effect which is rescued by valproic acid.

genetics↗

bioRxiv2017

Leveraging lung tissue transcriptome to uncover candidate causal genes in COPD genetic associations

We collated 129 non-overlapping risk loci for chronic obstructive pulmonary disease (COPD) from the GWAS literature. Using recent and complementary integrative genomics approaches, combining GWAS and lung eQTL results, we identified 12 novel COPD loci and corresponding causal genes. In addition, we mapped candidate causal genes for 60 out of the 129 GWAS-nominated loci as well as for four sub-genome-wide significant COPD risk loci derived from the largest GWAS on COPD. Mapping causal genes in lung tissue represents an important contribution on the genetics of COPD, enriches our biological interpretation of GWAS findings, and brings us closer to clinical translation of genetic associations.

genomics↗

bioRxiv2017

Genetic Analysis of Deep Phenotyping Projects in Common Disorders

Several studies of complex psychotic disorders with large numbers of neurobiological phenotypes are currently under way, in living patients and controls, and on assemblies of brain specimens. Genetic analyses of such data typically present challenges, because of the choice of underlying hypotheses on genetic architecture of the studied disorders and phenotypes, large numbers of phenotypes, the appropriate multiple testing corrections, limited numbers of subjects, imputations required on missing phenotypes and genotypes, and the cross-disciplinary nature of the phenotype measures. Advances in genotype and phenotype imputation, and in genome-wide association (GWAS) methods, are useful in dealing with these challenges. As compared with the more traditional single-trait analyses, deep phenotyping with simultaneous genome-wide analyses serves as a discovery tool for previously unsuspected relationships of phenotypic traits with each other, and with specific molecular involvements.

genetics↗

bioRxiv2017

Large-scale screening of rare genetic variants in humans reveals frequent splicing disruptions

Any individuals genome contains [~]4-5 million genetic variants that differ from reference, and understanding how these variants give rise to trait diversity and disease susceptibility is a central goal of human genetics1. A vast majority (96-99%) of an individuals variants are common, though at a population level the overwhelming majority of variants are rare2-5. Because of their scarcity in an individuals genome, rare variants that play important roles in complex traits are likely to have large functional effects6,7. Mutations that cause an exon to be skipped can have severe functional consequences on gene function, and many known disease-causing mutations reduce or eliminate exon recognition8. Here we explore the extent to which rare genetic variation in humans results in near complete loss of exon recognition. We developed a Multiplexed Functional Assay of Splicing using Sort-seq (MFASS) that allows us to measure exon inclusion in thousands of human exons and surrounding intronic sequence simultaneously. We assayed 27,733 extant variants in the Exome Aggregation Consortium (ExAC)9 within or adjacent to 2,339 human exons, and found that 3.8% (1,050) of the variants, almost all of which were extremely rare, led to large-effect defects in exon recognition. Importantly, we find that 83% of these splice-disrupting variants (SDVs) are located outside of canonical splice sites, are distributed evenly across distinct exonic and intronic regions, and are difficult to predict a priori. Our results indicate that loss of exon recognition is an important and underappreciated means by which rare variants exert large functional effects, and that MFASS enables their empirical assessment for splicing defects at scale.

genetics↗

bioRxiv2017

Modernized tools for streamlined genetic manipulation of wild and diverse symbiotic bacteria

The capacity to associate symbiotic bacteria with vital aspects of plant and animal biology is outpacing our understanding of the mechanisms shaping these interactions. A major barrier to mechanistic studies is the paucity of tools for genetically manipulating wild and diverse bacterial isolates. Solving this problem is crucial to elucidating the cellular and molecular rules that govern symbiotic relationships and ultimately harnessing them for agricultural and biomedical applications. Therefore, we constructed a series of vectors that expedite genetic knock-in and knock-out procedures across a range of bacterial lineages. This was accomplished by developing strategies for domestication-free bacterial conjugation, designing plasmids with customizable features, and streamlining allelic exchange using visual markers of homologous recombination. These tools enabled a comparative study based on live imaging of diverse bacterial symbionts native to the zebrafish intestine, with which we discovered heterogeneous colonization patterns and a striking correlation between bacterial population biogeography and cellular behavior.

genetics↗