More Similar than Different: Memory, Executive Functions, Cortical Thickness, and Glucose Metabolism in Biomarker-Positive Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia.

Background: Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are typically associated with very different clinical and neuroanatomical presentations; however, there is increasing recognition of similarities. Objective: To examine memory and executive functions, as well as cortical thickness, and glucose metabolism in AD and bvFTD signature brain regions. Methods: We compared differences in a group of biomarker-defined participants with Alzheimer's disease and a group of clinically diagnosed participants with bvFTD. These groups were also contrasted with healthy controls (HC). Results: As expected, memory functions were generally more impaired in AD, followed by bvFTD, and both clinical groups performed more poorly than the HC group. Executive function measures were similar in AD compared to bvFTD for motor sequencing and go/no-go, but bvFTD had more difficulty with a set shifting task. Participants with AD showed thinner cortex and lower glucose metabolism in the angular gyrus compared to bvFTD. Participants with bvFTD had thinner cortex in the insula and temporal pole relative to AD and healthy controls, but otherwise the two clinical groups were similar for other frontal and temporal signature regions. Conclusions: Overall, the results of this study highlight more similarities than differences between AD and bvFTD in terms of cognitive functions, cortical thickness, and glucose metabolism. Further research is needed to better understand the mechanisms mediating this overlap and how these relationships evolve longitudinally.

Pleiotropic loci for cannabis use disorder severity in multi-ancestry high-risk populations.

Cannabis use disorder (CUD) is common and has in part a genetic basis. The risk factors underlying its development likely involve multiple genes that are polygenetic and interact with each other and the environment to ultimately lead to the disorder. Co-morbidity and genetic correlations have been identified between CUD and other disorders and traits in select populations primarily of European descent. If two or more traits, such as CUD and another disorder, are affected by the same genetic locus, they are said to be pleiotropic. The present study aimed to identify specific pleiotropic loci for the severity level of CUD in three high-risk population cohorts: American Indians (AI), Mexican Americans (MA), and European Americans (EA). Using a previously developed computational method based on a machine learning technique, we leveraged the entire GWAS catalog and identified 114, 119, and 165 potentially pleiotropic variants for CUD severity in AI, MA, and EA respectively. Ten pleiotropic loci were shared between the cohorts although the exact variants from each cohort differed. While majority of the pleiotropic genes were distinct in each cohort, they converged on numerous enriched biological pathways. The gene ontology terms associated with the pleiotropic genes were predominately related to synaptic functions and neurodevelopment. Notable pathways included Wnt/ß-catenin signaling, lipoprotein assembly, response to UV radiation, and components of the complement system. The pleiotropic genes were the most significantly differentially expressed in frontal cortex and coronary artery, up-regulated in adipose tissue, and down-regulated in testis, prostate, and ovary. They were significantly up-regulated in most brain tissues but were down-regulated in the cerebellum and hypothalamus. Our study is the first to attempt a large-scale pleiotropy detection scan for CUD severity. Our findings suggest that the different population cohorts may have distinct genetic factors for CUD, however they share pleiotropic genes from underlying pathways related to Alzheimer's disease, neuroplasticity, immune response, and reproductive endocrine systems.

Focused ultrasound-mediated blood-brain barrier opening in Alzheimer's disease: long-term safety, imaging, and cognitive outcomes.

OBJECTIVE: MRI-guided low-intensity focused ultrasound (FUS) has been shown to reversibly open the blood-brain barrier (BBB), with the potential to deliver therapeutic agents noninvasively to target brain regions in patients with Alzheimer's disease (AD) and other neurodegenerative conditions. Previously, the authors reported the short-term safety and feasibility of FUS BBB opening of the hippocampus and entorhinal cortex (EC) in patients with AD. Given the need to treat larger brain regions beyond the hippocampus and EC, brain volumes and locations treated with FUS have now expanded. To evaluate any potential adverse consequences of BBB opening on disease progression, the authors report safety, imaging, and clinical outcomes among participants with mild AD at 6-12 months after FUS treatment targeted to the hippocampus, frontal lobe, and parietal lobe. METHODS: In this open-label trial, participants with mild AD underwent MRI-guided FUS sonication to open the BBB in ß-amyloid positive regions of the hippocampus, EC, frontal lobe, and parietal lobe. Participants underwent 3 separate FUS treatment sessions performed 2 weeks apart. Outcome assessments included safety, imaging, neurological, cognitive, and florbetaben ß-amyloid PET. RESULTS: Ten participants (range 55-76 years old) completed 30 separate FUS treatments at 2 participating institutions, with 6-12 months of follow-up. All participants had immediate BBB opening after FUS and BBB closure within 24-48 hours. All FUS treatments were well tolerated, with no serious adverse events related to the procedure. All 10 participants had a minimum of 6 months of follow-up, and 7 participants had a follow-up out to 1 year. Changes in the Alzheimer's Disease Assessment Scale-cognitive and Mini-Mental State Examination scores were comparable to those in controls from the Alzheimer's Disease Neuroimaging Initiative. PET scans demonstrated an average ß-amyloid plaque of 14% in the Centiloid scale in the FUS-treated regions. CONCLUSIONS: This study is the largest cohort of participants with mild AD who received FUS treatment, and has the longest follow-up to date. Safety was demonstrated in conjunction with reversible and repeated BBB opening in multiple cortical and deep brain locations, with a concomitant reduction of ß-amyloid. There was no apparent cognitive worsening beyond expectations up to 1 year after FUS treatment, suggesting that the BBB opening treatment in multiple brain regions did not adversely influence AD progression. Further studies are needed to determine the clinical significance of these findings. FUS offers a unique opportunity to decrease amyloid plaque burden as well as the potential to deliver targeted therapeutics to multiple brain regions in patients with neurodegenerative disorders.

Association of Predicted Expression and Multimodel Association Analysis of Substance Abuse Traits.

Introduction: Genome-wide association studies (GWAS) have played a critical role in identifying many thousands of loci associated with complex phenotypes and diseases. This has led to several translations of novel disease susceptibility genes into drug targets and care. This however has not been the case for analyses where sample sizes are small, which suffer from multiple comparisons testing. The present study examined the statistical impact of combining a burden test methodology, PrediXcan, with a multimodel meta-analysis, cross phenotype association (CPASSOC). Methods: The analysis was conducted on 5 addiction traits: family alcoholism, cannabis craving, alcohol, nicotine, and cannabis dependence and 10 brain tissues: anterior cingulate cortex BA24, cerebellar hemisphere, cortex, hippocampus, nucleus accumbens basal ganglia, caudate basal ganglia, cerebellum, frontal cortex BA9, hypothalamus, and putamen basal ganglia. Our sample consisted of 1,640 participants from the University of California, San Francisco (UCSF) Family Alcoholism Study. Genotypes were obtained through low pass whole genome sequencing and the use of Thunder, a linkage disequilibrium variant caller. Results: The post-PrediXcan, gene-phenotype association without aggregation resulted in 2 significant results, HCG27 and SPPL2B. Aggregating across phenotypes resulted no significant findings. Aggregating across tissues resulted in 15 significant and 5 suggestive associations: PPIE, RPL36AL, FOXN2, MTERF4, SEPTIN2, CIAO3, RPL36AL, ZNF304, CCDC66, SSPOP, SLC7A9, LY75, MTRF1L, COA5, and RRP7A; RPS23, GNMT, ERV3-1, APIP, and HLA-B, respectively. Discussion: Given the relatively small size of the cohort, this multimodel approach was able to find over a dozen significant associations between predicted gene expression and addiction traits. Of our findings, 8 had prior associations with similar phenotypes through investigation of the GWAS Atlas. With the onset of improved transcriptome data, this approach should increase in efficacy.

A greedy regression algorithm with coarse weights offers novel advantages.

Regularized regression analysis is a mature analytic approach to identify weighted sums of variables predicting outcomes. We present a novel Coarse Approximation Linear Function (CALF) to frugally select important predictors and build simple but powerful predictive models. CALF is a linear regression strategy applied to normalized data that uses nonzero weights + 1 or - 1. Qualitative (linearly invariant) metrics to be optimized can be (for binary response) Welch (Student) t-test p-value or area under curve (AUC) of receiver operating characteristic, or (for real response) Pearson correlation. Predictor weighting is critically important when developing risk prediction models. While counterintuitive, it is a fact that qualitative metrics can favor CALF with ± 1 weights over algorithms producing real number weights. Moreover, while regression methods may be expected to change most or all weight values upon even small changes in input data (e.g., discarding a single subject of hundreds) CALF weights generally do not so change. Similarly, some regression methods applied to collinear or nearly collinear variables yield unpredictable magnitude or the direction (in p-space) of the weights as a vector. In contrast, with CALF if some predictors are linearly dependent or nearly so, CALF simply chooses at most one (the most informative, if any) and ignores the others, thus avoiding the inclusion of two or more collinear variables in the model.

Noninvasive prenatal exome sequencing diagnostic utility limited by sequencing depth and fetal fraction.

OBJECTIVE: Sequencing cell-free DNA now allows detection of large chromosomal abnormalities and dominant Mendelian disorders in the prenatal period. Improving upon these methods would allow newborn screening programs to begin with prenatal genetics, ultimately improving the management of rare genetic disorders. METHODS: As a pilot study, we performed exome sequencing on the cell-free DNA from three mothers with singleton pregnancies to assess the viability of broad sequencing modalities in a noninvasive prenatal setting. RESULTS: We found poor resolution of maternal and fetal genotypes due to both sampling and technical issues. CONCLUSION: We find broad sequencing modalities inefficient for noninvasive prenatal applications. Alternatively, we suggest a more targeted path forward for noninvasive prenatal genotyping.

Effects of genetic risk for alcohol dependence and onset of regular drinking on the progression to alcohol dependence: A polygenic risk score approach.

BACKGROUND: Prior studies have established the importance of genetic contributions to the etiology of alcohol dependence (AD), and suggested an early onset of alcohol use represents an initial marker of this genetic risk, which is associated with a more rapid progression to AD and increased risk for AD itself. Building on prior work, the current study examined whether the additive effects of AD risk variants predicted the rate of progression to AD from the onset of regular drinking, a drinking milestone with high clinical relevance to AD prevention. METHODS: Data from 1501 European-ancestry adults from the University of California - San Francisco Family Alcoholism Study were used to examine whether polygenic risk scores for AD (PRSAD) and age-at-onset of regular drinking contributed uniquely to the likelihood of having a lifetime AD diagnosis and the rate of progression from regular drinking to AD. Mixed effects logistic regression and Cox proportional hazards regression analyses were employed. RESULTS: Increases in PRSAD were associated with a faster progression from regular drinking to AD independent of age-at-onset of regular drinking. An independent effect of age-at-onset of regular drinking was also observed indicating that a one-year delay in regular drinking was associated with a 7% decrease in the hazard of progression to AD among drinkers with an early onset (≤ 18), but a 3% increase among drinkers with a late onset (> 18) of regular drinking. CONCLUSIONS: These results broaden our understanding of the contributions of measured genotypes underlying AD-risk on the etiology and clinical course of AD.

Pre-capture multiplexing provides additional power to detect copy number variation in exome sequencing.

BACKGROUND: As exome sequencing (ES) integrates into clinical practice, we should make every effort to utilize all information generated. Copy-number variation can lead to Mendelian disorders, but small copy-number variants (CNVs) often get overlooked or obscured by under-powered data collection. Many groups have developed methodology for detecting CNVs from ES, but existing methods often perform poorly for small CNVs and rely on large numbers of samples not always available to clinical laboratories. Furthermore, methods often rely on Bayesian approaches requiring user-defined priors in the setting of insufficient prior knowledge. This report first demonstrates the benefit of multiplexed exome capture (pooling samples prior to capture), then presents a novel detection algorithm, mcCNV ("multiplexed capture CNV"), built around multiplexed capture. RESULTS: We demonstrate: (1) multiplexed capture reduces inter-sample variance; (2) our mcCNV method, a novel depth-based algorithm for detecting CNVs from multiplexed capture ES data, improves the detection of small CNVs. We contrast our novel approach, agnostic to prior information, with the the commonly-used ExomeDepth. In a simulation study mcCNV demonstrated a favorable false discovery rate (FDR). When compared to calls made from matched genome sequencing, we find the mcCNV algorithm performs comparably to ExomeDepth. CONCLUSION: Implementing multiplexed capture increases power to detect single-exon CNVs. The novel mcCNV algorithm may provide a more favorable FDR than ExomeDepth. The greatest benefits of our approach derive from (1) not requiring a database of reference samples and (2) not requiring prior information about the prevalance or size of variants.

Common genetic substrates of alcohol and substance use disorder severity revealed by pleiotropy detection against GWAS catalog in two populations.

Alcohol and other substance use disorders (AUD and SUD) are complex diseases that are postulated to have a polygenic inheritance and are often comorbid with other disorders. The comorbidities may arise partially through genetic pleiotropy. Identification of specific gene variants accounting for large parts of the variance in these disorders has yet to be accomplished. We describe a flexible strategy that takes a variant-trait association database and determines if a subset of disease/straits are potentially pleiotropic with the disorder under study. We demonstrate its usage in a study of use disorders in two independent cohorts: alcohol, stimulants, cannabis (CUD), and multi-substance use disorders (MSUD) in American Indians (AI) and AUD and CUD in Mexican Americans (MA). Using a machine learning method with variants in GWAS catalog, we identified 229 to 246 pleiotropic variants for AI and 153 to 160 for MA for each SUD. Inflammation was the most enriched for MSUD and AUD in AIs. Neurological disorder was the most significantly enriched for CUD in both cohorts, and for AUD and stimulants in AIs. Of the select pleiotropic genes shared among substances-cohorts, multiple biological pathways implicated in SUD and other psychiatric disorders were enriched, including neurotrophic factors, immune responses, extracellular matrix, and circadian regulation. Shared pleiotropic genes were significantly up-regulated in brain regions playing important roles in SUD, down-regulated in esophagus mucosa, and differentially regulated in adrenal gland. This study fills a gap for pleiotropy detection in understudied admixed populations and identifies pleiotropic variants that may be potential targets of interest for SUD.

SMNN: batch effect correction for single-cell RNA-seq data via supervised mutual nearest neighbor detection.

Batch effect correction has been recognized to be indispensable when integrating single-cell RNA sequencing (scRNA-seq) data from multiple batches. State-of-the-art methods ignore single-cell cluster label information, but such information can improve the effectiveness of batch effect correction, particularly under realistic scenarios where biological differences are not orthogonal to batch effects. To address this issue, we propose SMNN for batch effect correction of scRNA-seq data via supervised mutual nearest neighbor detection. Our extensive evaluations in simulated and real datasets show that SMNN provides improved merging within the corresponding cell types across batches, leading to reduced differentiation across batches over MNN, Seurat v3 and LIGER. Furthermore, SMNN retains more cell-type-specific features, partially manifested by differentially expressed genes identified between cell types after SMNN correction being biologically more relevant, with precision improving by up to 841.0%.

Projected t-SNE for batch correction.

MOTIVATION: Low-dimensional representations of high-dimensional data are routinely employed in biomedical research to visualize, interpret and communicate results from different pipelines. In this article, we propose a novel procedure to directly estimate t-SNE embeddings that are not driven by batch effects. Without correction, interesting structure in the data can be obscured by batch effects. The proposed algorithm can therefore significantly aid visualization of high-dimensional data. RESULTS: The proposed methods are based on linear algebra and constrained optimization, leading to efficient algorithms and fast computation in many high-dimensional settings. Results on artificial single-cell transcription profiling data show that the proposed procedure successfully removes multiple batch effects from t-SNE embeddings, while retaining fundamental information on cell types. When applied to single-cell gene expression data to investigate mouse medulloblastoma, the proposed method successfully removes batches related with mice identifiers and the date of the experiment, while preserving clusters of oligodendrocytes, astrocytes, and endothelial cells and microglia, which are expected to lie in the stroma within or adjacent to the tumours. AVAILABILITY AND IMPLEMENTATION: Source code implementing the proposed approach is available as an R package at https://github.com/emanuelealiverti/BC_tSNE, including a tutorial to reproduce the simulation studies. CONTACT: aliverti@stat.unipd.it.

Effects of Common and Rare Chromosome 4 GABAergic Gene Variation on Alcohol Use and Antisocial Behavior.

OBJECTIVE: Epidemiological estimates suggest that nearly half of individuals diagnosed with alcohol use disorder will be diagnosed with another mental health disorder, with strong associations involving other externalizing disorders. Molecular genetic studies investigating the relation between alcohol use disorder and externalizing behaviors (e.g., antisocial behavior) have focused on a cluster of chromosome 4 γ-aminobutyric acid (GABA) receptor genes (GABRG1-A2-A4-B1) but have generated varying results. METHOD: The current study examined associations between common and rare variation in this region with alcohol use disorder and antisocial behavior using genetic sequencing data. Specifically, the University of California at San Francisco Family Alcoholism Sample (n = 1,610; 62% female) was used to conduct common and rare variant association tests in the GABRG1-A2-A4-B1 cluster with DSM-5 alcohol use disorder symptom counts, antisocial behavior, and a product term representing their interaction. RESULTS: Gene-based analyses of rare variation resulted in a significant association between rare GABRA2 variation and the interaction term. Single-variant analysis yielded only nominally significant associations. The strongest association for alcohol use disorder (rs3756007) was located in GABRA2, the strongest association for antisocial behavior (rs11941860) was located in GABRG1, and the interaction term yielded top associations in GABRA2 (rs2119183) and the intergenic region between GABRA2 and GABRG1 (rs536599). Common and rare variant associations for the interaction remained similar when covarying for the effects of the other type of variation, suggesting that the significant rare variant signal is independent of common variant contributions. CONCLUSIONS: The present study suggests that both rare and common variant associations in GABRA2 confer risk for alcohol use disorder and antisocial behaviors, indicating a potential liability toward externalizing behavior more broadly.

Genetic loci for alcohol-related life events and substance-induced affective symptoms: indexing the "dark side" of addiction.

A limited number of genetic variants have been identified in traditional GWAS as risk or protective factors for alcohol use disorders (AUD) and related phenotypes. We herein report whole-genome association and rare-variant analyses on AUD traits in American Indians (AI) and European Americans (EA). We evaluated 742 AIs and 1711 EAs using low-coverage whole-genome sequencing. Phenotypes included: (1) a metric based on the occurrence of 36 alcohol-related life events that reflect AUD severity; (2) two alcohol-induced affective symptoms that accompany severe AUDs. We identified two new loci for alcohol-related life events with converging evidence from both cohorts: rare variants of K2P channel gene KCNK2, and rare missense and splice-site variants in pro-inflammatory mediator gene PDE4C. A NAF1-FSTL5 intergenic variant and an FSTL5 variant were respectively associated with alcohol-related life events in AI and EA. PRKG2 of serine/threonine protein kinase family, and rare variants in interleukin subunit gene EBI3 (IL-27B) were uniquely associated with alcohol-induced affective symptoms in AI. LncRNA LINC02347 on 12q24.32 was uniquely associated with alcohol-induced depression in EA. The top GWAS findings were primarily rare/low-frequency variants in AI, and common variants in EA. Adrenal gland was the most enriched in tissue-specific gene expression analysis for alcohol-related life events, and nucleus accumbens was the most enriched for alcohol-induced affective states in AI. Prefrontal cortex was the most enriched in EA for both traits. These studies suggest that whole-genome sequencing can identify novel, especially uncommon, variants associated with severe AUD phenotypes although the findings may be population specific.

Indexing the 'dark side of addiction': substance-induced affective symptoms and alcohol use disorders.

BACKGROUND AND AIMS: The emergence of negative affective symptoms during the course of alcohol use disorders (AUDs) (e.g. 'dark side' symptoms) has been suggested theoretically; however, the description of their occurrence is limited. This study operationalized two negative affect symptoms and tested the strength of association between these phenotypes and (1) indicators of the clinical course of the severity of AUD, (2) comorbid Axis I psychiatric disorders, suicidal behaviors and trait neuroticism and (3) whether participants reported drinking to relieve the negative affective symptoms. DESIGN: A retrospective cross-sectional study was used to evaluate associations, using logistic regression, between the two negative affective symptoms and clinical measures of AUD severity and progression as well as comorbidity with other psychiatric disorders and conditions, adjusted for demographic characteristics. SETTING: US community-based studies. PARTICIPANTS: A total of 2568 individuals with AUDs obtained from larger population studies that targeted individuals of European American (n = 1663), Mexican American and American Indian (n = 905) ancestry. MEASUREMENTS: Semi-Structured Assessment for the Genetics of Alcoholism was used to ascertain the two 'dark side' phenotypes, clinical diagnoses, the clinical course of AUD and associated symptoms. The two phenotypes were: (1) being anxious or depressed when trying to cut down or stop drinking and (2) experiencing disabling depression for more than 24 hours while drinking. FINDINGS: Both phenotypes were found to be rare in mild and moderate use disorder and highly prevalent in severe AUDs. Having an independent anxiety or affective disorder and elevated scores on trait neuroticism were also associated significantly with the occurrence of both symptoms, as was alcohol 'craving', elevated treatment-seeking, suicidal behaviors and drinking to relieve the symptoms. CONCLUSIONS: Affective symptoms are common in severe alcohol use disorders are associated with a history of independent affective/anxiety disorders, neuroticism and suicidal behaviors; and may promote further heavy drinking.

Increasing the diagnostic yield of exome sequencing by copy number variant analysis.

As whole exome sequencing (WES) becomes more widely used in the clinical realm, a wealth of unanalyzed information will be routinely generated. Using WES read depth data to predict copy number variation (CNV) could extend the diagnostic utility of this previously underutilized data by providing clinically important information such as previously unsuspected deletions or duplications. We evaluated ExomeDepth, a free R package, in addition to an aneuploidy prediction method, to detect CNVs in WES data. First, in a blinded pilot study, five out of five genomic alterations were correctly identified from clinical samples with previously defined chromosomal gains or losses, including submicroscopic deletions, duplications, and chromosomal trisomy. We then examined CNV calls among 53 patients participating in the NCGENES research study and undergoing WES, who had existing clinical chromosomal microarray (CMA) data that could be used for validation. For unique CNVs that overlap well with WES coverage regions, sensitivity was 89% for deletions and 65% for duplications. While specificity of the algorithm calls remains a concern, this is less of an issue at high threshold filtering levels. When applied to all 672 patients from the exome sequencing study, ExomeDepth identified eleven diagnostically relevant CNVs ranging in size from a two exon deletion to whole chromosome duplications, as well as numerous other CNVs with varying clinical significance. This opportunistic analysis of WES data yields an additional 1.6% of patients in this study with pathogenic or likely pathogenic CNVs that are clinically relevant to their phenotype as well as clinically relevant secondary findings. Finally, we demonstrate the potential value of copy number analysis in cases where a single heterozygous likely or known pathogenic single nucleotide alteration is identified in a gene associated with an autosomal recessive condition.

Genome-wide association study and meta-analysis identify loci associated with ventricular and supraventricular ectopy.

The genetic basis of supraventricular and ventricular ectopy (SVE, VE) remains largely uncharacterized, despite established genetic mechanisms of arrhythmogenesis. To identify novel genetic variants associated with SVE/VE in ancestrally diverse human populations, we conducted a genome-wide association study of electrocardiographically identified SVE and VE in five cohorts including approximately 43,000 participants of African, European and Hispanic/Latino ancestry. In thirteen ancestry-stratified subgroups, we tested multivariable-adjusted associations of SVE and VE with single nucleotide polymorphism (SNP) dosage. We combined subgroup-specific association estimates in inverse variance-weighted, fixed-effects and Bayesian meta-analyses. We also combined fixed-effects meta-analytic t-test statistics for SVE and VE in multi-trait SNP association analyses. No loci reached genome-wide significance in trans-ethnic meta-analyses. However, we found genome-wide significant SNPs intronic to an apoptosis-enhancing gene previously associated with QRS interval duration (FAF1; lead SNP rs7545860; effect allele frequency = 0.02; P = 2.0 × 10-8) in multi-trait analysis among European ancestry participants and near a locus encoding calcium-dependent glycoproteins (DSC3; lead SNP rs8086068; effect allele frequency = 0.17) in meta-analysis of SVE (P = 4.0 × 10-8) and multi-trait analysis (P = 2.9 × 10-9) among African ancestry participants. The novel findings suggest several mechanisms by which genetic variation may predispose to ectopy in humans and highlight the potential value of leveraging pleiotropy in future studies of ectopy-related phenotypes.

Dissecting the Causal Mechanism of X-Linked Dystonia-Parkinsonism by Integrating Genome and Transcriptome Assembly.

X-linked Dystonia-Parkinsonism (XDP) is a Mendelian neurodegenerative disease that is endemic to the Philippines and is associated with a founder haplotype. We integrated multiple genome and transcriptome assembly technologies to narrow the causal mutation to the TAF1 locus, which included a SINE-VNTR-Alu (SVA) retrotransposition into intron 32 of the gene. Transcriptome analyses identified decreased expression of the canonical cTAF1 transcript among XDP probands, and de novo assembly across multiple pluripotent stem-cell-derived neuronal lineages discovered aberrant TAF1 transcription that involved alternative splicing and intron retention (IR) in proximity to the SVA that was anti-correlated with overall TAF1 expression. CRISPR/Cas9 excision of the SVA rescued this XDP-specific transcriptional signature and normalized TAF1 expression in probands. These data suggest an SVA-mediated aberrant transcriptional mechanism associated with XDP and may provide a roadmap for layered technologies and integrated assembly-based analyses for other unsolved Mendelian disorders.

Diagnostic utility of exome sequencing in the evaluation of neuromuscular disorders.

OBJECTIVE: To evaluate the diagnostic yield and workflow of genome-scale sequencing in patients with neuromuscular disorders (NMDs). METHODS: We performed exome sequencing in 93 undiagnosed patients with various NMDs for whom a molecular diagnosis was not yet established. Variants on both targeted and broad diagnostic gene lists were identified. Prior diagnostic tests were extracted from the patient's medical record to evaluate the use of exome sequencing in the context of their prior diagnostic workup. RESULTS: The overall diagnostic yield of exome sequencing in our cohort was 12.9%, with one or more pathogenic or likely pathogenic variants identified in a causative gene associated with the patient's disorder. Targeted gene lists had the same diagnostic yield as a broad NMD gene list in patients with clear neuropathy or myopathy phenotypes, but evaluation of a broader set of disease genes was needed for patients with complex NMD phenotypes. Most patients with NMD had undergone prior testing, but only 10/16 (63%) of these procedures, such as muscle biopsy, were informative in pointing to a final molecular diagnosis. CONCLUSIONS: Genome-scale sequencing or analysis of a panel of relevant genes used early in the evaluation of patients with NMDs can provide or clarify a diagnosis and minimize invasive testing in many cases.

Whole genome sequence study of cannabis dependence in two independent cohorts.

Recent advances in genome wide sequencing techniques and analytical methods allow for more comprehensive examinations of the genome than microarray-based genome-wide association studies (GWAS). The present report provides the first application of whole genome sequencing (WGS) to identify low frequency variants involved in cannabis dependence across two independent cohorts. The present study used low-coverage whole genome sequence data to conduct set-based association and enrichment analyses of low frequency variation in protein-coding regions as well as regulatory regions in relation to cannabis dependence. Two cohorts were studied: a population-based Native American tribal community consisting of 697 participants nested within large multi-generational pedigrees and a family-based sample of 1832 predominantly European ancestry participants largely nested within nuclear families. Participants in both samples were assessed for Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) lifetime cannabis dependence, with 168 and 241 participants receiving a positive diagnosis in each sample, respectively. Sequence kernel association tests identified one protein-coding region, C1orf110 and one regulatory region in the MEF2B gene that achieved significance in a meta-analysis of both samples. A regulatory region within the PCCB gene, a gene previously associated with schizophrenia, exhibited a suggestive association. Finally, a significant enrichment of regions within or near genes with multiple splice variants or involved in cell adhesion or potassium channel activity were associated with cannabis dependence. This initial study demonstrates the potential utility of low pass whole genome sequencing for identifying genetic variants involved in the etiology of cannabis use disorders.

Genetic Influences on Evening Preference Overlap with Those for Bipolar Disorder in a Sample of Mexican Americans and American Indians.

Diurnal preference (e.g., being an owl or lark) has been associated with several psychiatric disorders including bipolar disorder (BP), major depressive disorder, and substance use disorders. Previous large-scale genome-wide association studies (GWAS) aimed at identifying genetic influences on diurnal preference have exclusively included subjects of European ancestry. This study examined the genetic architecture of diurnal preference in two minority samples: a young adult sample of Mexican Americans (MAs), and a family-based sample of American Indians (AIs). Typed or imputed variants from exome chip data from the MA sample and low pass whole-genome sequencing from the AI cohort were analyzed using a mixed linear model approach for association with being an owl, as defined by a usual bedtime after 23:00 hrs. Genetic risk score (GRS) profiling detected shared genetic risk between evening preference and related disorders. Four variants in KIAA1549 like (KIAA1549L), a gene previously associated with attempted suicide in bipolar patients, were suggestively associated with being an owl at p < 1.82E-05; post hoc analyses showed the top variant trending in both the MA and AI cohorts at p = 2.50E-05 and p = .030, respectively. Variants associated with BP at p < .03 from the Psychiatric Genomics Consortium nominally predicted being an owl in the MA/AI cohort at p = .012. This study provides some additional evidence that genetic risk factors for BP also confer risk for being an owl in MAs/AIs and that evening preference may be a useful endophenotype for future studies of BP.