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Depression is a common condition, but current treatments are only effective in a subset of individuals. To identify new treatment targets, we integrated depression genome-wide association study (GWAS) results (N = 500,199) with human brain proteomes (N = 376) to perform a proteome-wide association study of depression followed by Mendelian randomization. We identified 19 genes that were consistent with being causal in depression, acting via their respective cis-regulated brain protein abundance. We replicated nine of these genes using an independent depression GWAS (N = 307,353) and another human brain proteomic dataset (N = 152). Eleven of the 19 genes also had cis-regulated mRNA levels that were associated with depression, based on integration of the depression GWAS with human brain transcriptomes (N = 888). Meta-analysis of the discovery and replication proteome-wide association study analyses identified 25 brain proteins consistent with being causal in depression, 20 of which were not previously implicated in depression by GWAS. Together, these findings provide promising brain protein targets for further mechanistic and therapeutic studies. Wingo et al. integrate depression GWAS results with human brain proteomes to perform proteome-wide association studies followed by Mendelian randomization. They identify 25 proteins as potential causal mediators of depression, of which 20 are new.

Genome-wide association studies (GWAS) have identified many risk loci for Alzheimer's disease (AD)1,2, but how these loci confer AD risk is unclear. Here, we aimed to identify loci that confer AD risk through their effects on brain protein abundance to provide new insights into AD pathogenesis. To that end, we integrated AD GWAS results with human brain proteomes to perform a proteome-wide association study (PWAS) of AD, followed by Mendelian randomization and colocalization analysis. We identified 11 genes that are consistent with being causal in AD, acting via their cis-regulated brain protein abundance. Nine replicated in a confirmation PWAS and eight represent new AD risk genes not identified before by AD GWAS. Furthermore, we demonstrated that our results were independent of APOE e4. Together, our findings provide new insights into AD pathogenesis and promising targets for further mechanistic and therapeutic studies.

Background The tumor microenvironment (TME) is increasingly appreciated as an important determinant of cancer outcome, including in multiple myeloma (MM). However, most myeloma microenvironment studies have been based on bone marrow (BM) aspirates, which often do not fully reflect the cellular content of BM tissue itself. To address this limitation in myeloma research, we systematically characterized the whole bone marrow (WBM) microenvironment during premalignant, baseline, on treatment, and post-treatment phases. Methods and findings Between 2004 and 2019, 998 BM samples were taken from 436 patients with newly diagnosed MM (NDMM) at the University of Arkansas for Medical Sciences in Little Rock, Arkansas, United States of America. These patients were 61% male and 39% female, 89% White, 8% Black, and 3% other/refused, with a mean age of 58 years. Using WBM and matched cluster of differentiation (CD)138-selected tumor gene expression to control for tumor burden, we identified a subgroup of patients with an adverse TME associated with 17 fewer months of progression-free survival (PFS) (95% confidence interval [CI] 5–29, 49–69 versus 70–82 months, χ2 p = 0.001) and 15 fewer months of overall survival (OS; 95% CI –1 to 31, 92–120 versus 113–129 months, χ2 p = 0.036). Using immunohistochemistry-validated computational tools that identify distinct cell types from bulk gene expression, we showed that the adverse outcome was correlated with elevated CD8+ T cell and reduced granulocytic cell proportions. This microenvironment develops during the progression of premalignant to malignant disease and becomes less prevalent after therapy, in which it is associated with improved outcomes. In patients with quantified International Staging System (ISS) stage and 70-gene Prognostic Risk Score (GEP-70) scores, taking the microenvironment into consideration would have identified an additional 40 out of 290 patients (14%, premutation p = 0.001) with significantly worse outcomes (PFS, 95% CI 6–36, 49–73 versus 74–90 months) who were not identified by existing clinical (ISS stage III) and tumor (GEP-70) criteria as high risk. The main limitations of this study are that it relies on computationally identified cell types and that patients were treated with thalidomide rather than current therapies. Conclusions In this study, we observe that granulocyte signatures in the MM TME contribute to a more accurate prognosis. This implies that future researchers and clinicians treating patients should quantify TME components, in particular monocytes and granulocytes, which are often ignored in microenvironment studies., Author summary Why was this study done? The cells around a tumor, also known as the tumor microenvironment (TME), can help a tumor grow by suppressing the immune system or fight a tumor by mounting an immune response. Most studies of multiple myeloma (MM) have focused on the tumor itself, rather than the bone marrow (BM) TME in which the tumor is growing. We hypothesized that the MM TME held clues that could help us better treat patients. What did the researchers do and find? We used a gene-expression–based computational technique to determine which cell types were present in patient BM. Patients with BM lacking a family of innate immune cells called granulocytes presented with worse outcomes compared to other patients. As MM progresses from a predisease to a cancerous state, the percentage of granulocytes decreases; the patients with the fewest granulocytes had more serious diseases. What do these findings mean? If granulocytes help myeloma patients respond to therapy, then addressing the decline in granulocytes may improve MM treatment. Patients with MM and few granulocytes in their BM should be watched for worse outcomes.

Genome-wide association studies (GWAS) have identified several risk loci for post-traumatic stress disorder (PTSD); however, how they confer PTSD risk remains unclear. We aimed to identify genes that confer PTSD risk through their effects on brain protein abundance to provide new insights into PTSD pathogenesis. To that end, we integrated human brain proteomes with PTSD GWAS results to perform a proteome-wide association study (PWAS) of PTSD, followed by Mendelian randomization, using a discovery and confirmatory study design. Brain proteomes (N = 525) were profiled from the dorsolateral prefrontal cortex using mass spectrometry. The Million Veteran Program (MVP) PTSD GWAS (n = 186,689) was used for the discovery PWAS, and the Psychiatric Genomics Consortium PTSD GWAS (n = 174,659) was used for the confirmatory PWAS. To understand whether genes identified at the protein-level were also evident at the transcript-level, we performed a transcriptome-wide association study (TWAS) using human brain transcriptomes (N = 888) and the MVP PTSD GWAS results. We identified 11 genes that contribute to PTSD pathogenesis via their respective cis-regulated brain protein abundance. Seven of 11 genes (64%) replicated in the confirmatory PWAS and 4 of 11 also had their cis-regulated brain mRNA levels associated with PTSD. High confidence level was assigned to 9 of 11 genes after considering evidence from the confirmatory PWAS and TWAS. Most of the identified genes are expressed in other PTSD-relevant brain regions and several are preferentially expressed in excitatory neurons, astrocytes, and oligodendrocyte precursor cells. These genes are novel, promising targets for mechanistic and therapeutic studies to find new treatments for PTSD.

Genetic changes that altered the function of gene regulatory elements have been implicated in the evolution of human traits such as the expansion of the cerebral cortex. However, identifying the particular changes that modified regulatory activity during human evolution remain challenging. Here we used massively parallel enhancer assays in neural stem cells to quantify the functional impact of >32,000 human-specific substitutions in >4,300 human accelerated regions (HARs) and human gain enhancers (HGEs), which include enhancers with novel activities in humans. We found that >30% of active HARs and HGEs exhibited differential activity between human and chimpanzee. We isolated the effects of human-specific substitutions from background genetic variation to identify the effects of genetic changes most relevant to human evolution. We found that substitutions interacted in both additive and nonadditive ways to modify enhancer function. Substitutions within HARs, which are highly constrained compared to HGEs, showed smaller effects on enhancer activity, suggesting that the impact of human-specific substitutions is buffered in enhancers with constrained ancestral functions. Our findings yield insight into how human-specific genetic changes altered enhancer function and provide a rich set of candidates for studies of regulatory evolution in humans.

The AD Knowledge Portal (adknowledgeportal.org) is a public data repository that shares data and other resources generated by multiple collaborative research programs focused on aging, dementia, and Alzheimer's disease (AD). In this article, we highlight how to use the Portal to discover and download genomic variant and transcriptomic data from the same individuals. First, we show how to use the web interface to browse and search for data of interest using relevant file annotations. We demonstrate how to learn more about the context surrounding the data, including diagnostic criteria and methodological details about sample preparation and data analysis. We present two primary ways to download data—using a web interface, and using a programmatic method that provides access using the command line. Finally, we show how to merge separate sources of metadata into a comprehensive file that contains factors and covariates necessary in downstream analyses. © 2020 The Authors. Basic Protocol 1: Find and download files associated with a selected study Basic Protocol 2: Download files in bulk using the command line client Basic Protocol 3: Working with file annotations and metadata

Background Alzheimer’s disease (AD) is an incurable neurodegenerative disease currently affecting 1.75% of the US population, with projected growth to 3.46% by 2050. Identifying common genetic variants driving differences in transcript expression that confer AD risk is necessary to elucidate AD mechanism and develop therapeutic interventions. We modify the FUSION transcriptome-wide association study (TWAS) pipeline to ingest gene expression values from multiple neocortical regions. Methods A combined dataset of 2003 genotypes clustered to 1000 Genomes individuals from Utah with Northern and Western European ancestry (CEU) was used to construct a training set of 790 genotypes paired to 888 RNASeq profiles from temporal cortex (TCX = 248), prefrontal cortex (FP = 50), inferior frontal gyrus (IFG = 41), superior temporal gyrus (STG = 34), parahippocampal cortex (PHG = 34), and dorsolateral prefrontal cortex (DLPFC = 461). Following within-tissue normalization and covariate adjustment, predictive weights to impute expression components based on a gene’s surrounding cis-variants were trained. The FUSION pipeline was modified to support input of pre-scaled expression values and support cross validation with a repeated measure design arising from the presence of multiple transcriptome samples from the same individual across different tissues. Results Cis-variant architecture alone was informative to train weights and impute expression for 6780 (49.67%) autosomal genes, the majority of which significantly correlated with gene expression; FDR N = 6775 (99.92%), Bonferroni: N = 6716 (99.06%). Validation of weights in 515 matched genotype to RNASeq profiles from the CommonMind Consortium (CMC) was (72.14%) in DLPFC profiles. Association of imputed expression components from all 2003 genotype profiles yielded 8 genes significantly associated with AD (FDR Conclusions We provide evidence of cis-genetic variation conferring AD risk through 8 genes across six distinct genomic loci. Moreover, we provide expression weights for 6780 genes as a valuable resource to the community, which can be abstracted across the neocortex and a wide range of neuronal phenotypes.

Genetic changes that altered the function of gene regulatory elements have been implicated in the evolution of the human brain. However, identifying the particular changes that modified regulatory activity during neurodevelopment remains challenging. Here we used massively parallel enhancer assays in human neural stem cells to measure the impact of 32,776 human-specific substitutions on enhancer activity in 1,363 Human Accelerated Regions (HARs) and 3,027 Human Gain Enhancers (HGEs), which include enhancers with novel activities in humans. We found that 31.9% of active HARs and 36.4% of active HGEs exhibited differential activity between human and chimpanzee. This enabled us to isolate the effects of 401 human-specific substitutions from other types of genetic variation in HARs and HGEs. Substitutions acted in both an additive and non-additive manner to alter enhancer activity. Human-specific substitutions altered predicted binding sites for a specific set of human transcription factors (TFs) that were a subset of TF binding sites associated with enhancer activity in our assay. Substitutions within HARs, which are overall highly constrained compared to HGEs, showed smaller effects on enhancer activity, suggesting that the impact of human-specific substitutions may be buffered in enhancers with constrained ancestral functions. Our findings yield insight into the mechanisms by which human-specific genetic changes impact enhancer function and provide a rich set of candidates for experimental studies of regulatory evolution in humans.

Changes in gene regulation have been linked to the expansion of the human cerebral cortex and to neurodevelopmental disorders. However, the biological effects of genetic variation within developmental regulatory elements on human corticogenesis are not well understood. We used sgRNA-Cas9 genetic screens in human neural stem cells (hNSCs) to disrupt 10,674 expressed genes and 2,227 enhancers active in the developing human cortex and determine the resulting effects on cellular proliferation. Gene disruptions affecting proliferation were enriched for genes associated with risk for human neurodevelopmental phenotypes including primary microcephaly and autism spectrum disorder. Although disruptions in enhancers had overall weaker effects on proliferation than gene disruptions, we identified enhancer disruptions that severely perturbed hNSC self-renewal. Disruptions in Human Accelerated Regions and Human Gain Enhancers, regulatory elements implicated in the evolution of the human brain, also perturbed hNSC proliferation, establishing a role for these elements in human neurodevelopment. Integrating proliferation phenotypes with chromatin interaction maps revealed regulatory relationships between enhancers and target genes that contribute to neurogenesis and potentially to human cortical evolution.

Summary: Whole-exome sequencing (WES) studies have demonstrated the contribution of de novo loss-of-function single-nucleotide variants (SNVs) to autism spectrum disorder (ASD). However, challenges in the reliable detection of de novo insertions and deletions (indels) have limited inclusion of these variants in prior analyses. By applying a robust indel detection method to WES data from 787 ASD families (2,963 individuals), we demonstrate that de novo frameshift indels contribute to ASD risk (OR = 1.6; 95% CI = 1.0–2.7; p = 0.03), are more common in female probands (p = 0.02), are enriched among genes encoding FMRP targets (p = 6 × 10−9), and arise predominantly on the paternal chromosome (p < 0.001). On the basis of mutation rates in probands versus unaffected siblings, we conclude that de novo frameshift indels contribute to risk in approximately 3% of individuals with ASD. Finally, by observing clustering of mutations in unrelated probands, we uncover two ASD-associated genes: KMT2E (MLL5), a chromatin regulator, and RIMS1, a regulator of synaptic vesicle release. : Insertions and deletions (indels) have proven especially difficult to detect in exome sequencing data. Dong et al. now identify indels in exome data for 787 autism spectrum disorder (ASD) families. They demonstrate association between de novo indels that alter the reading frame and ASD. Furthermore, by observing clustering of indels in unrelated probands, they uncover two additional ASD-associated genes: KMT2E (MLL5), a chromatin regulator, and RIMS1, a regulator of synaptic vesicle release.

Morphological innovations such as the mammalian neocortex may involve the evolution of novel regulatory sequences. However, de novo birth of regulatory elements active during morphogenesis has not been extensively studied in mammals. Here, we use H3K27ac-defined regulatory elements active during human and mouse corticogenesis to identify enhancers that were likely active in the ancient mammalian forebrain. We infer the phylogenetic origins of these enhancers and find that ∼20% arose in the mammalian stem lineage, coincident with the emergence of the neocortex. Implementing a permutation strategy that controls for the nonrandom variation in the ages of background genomic sequences, we find that mammal-specific enhancers are overrepresented near genes involved in cell migration, cell signaling, and axon guidance. Mammal-specific enhancers are also overrepresented in modules of coexpressed genes in the cortex that are associated with these pathways, notably ephrin and semaphorin signaling. Our results also provide insight into the mechanisms of regulatory innovation in mammals. We find that most neocortical enhancers did not originate by en bloc exaptation of transposons. Young neocortical enhancers exhibit smaller H3K27ac footprints and weaker evolutionary constraint in eutherian mammals than older neocortical enhancers. Based on these observations, we present a model of the enhancer life cycle in which neocortical enhancers initially emerge from genomic background as short, weakly constrained "proto-enhancers." Many proto-enhancers are likely lost, but some may serve as nucleation points for complex enhancers to evolve.

Introduction The multiple myeloma (MM) tumor microenvironment (TME) strongly influences patient outcomes as evidenced by the success of immunomodulatory therapies. To develop precision immunotherapeutic approaches, it is essential to identify and enumerate TME cell types and understand their dynamics. Methods We estimated the population of immune and other non-tumor cell types during the course of MM treatment at a single institution using gene expression of paired CD138-selected bone marrow aspirates and whole bone marrow (WBM) core biopsies from 867 samples of 436 newly diagnosed MM patients collected at 5 time points: pre-treatment (N=354), post-induction (N=245), post-transplant (N=83), post-consolidation (N=51), and post-maintenance (N=134). Expression profiles from the aspirates were used to infer the transcriptome contribution of immune and stromal cells in the WBM array data. Unsupervised clustering of these non-tumor gene expression profiles across all time points was performed using the R package ConsensusClusterPlus with Bayesian Information Criterion (BIC) to select the number of clusters. Individual cell types in these TMEs were estimated using the DCQ algorithm and a gene expression signature matrix based on the published LM22 leukocyte matrix (Newman et al., 2015) augmented with 5 bone marrow- and myeloma-specific cell types. Results Our deconvolution approach accurately estimated percent tumor cells in the paired samples compared to estimates from microscopy and flow cytometry (PCC = 0.63, RMSE = 9.99%). TME clusters built on gene expression data from all 867 samples resulted in 5 unsupervised clusters covering 91% of samples. While the fraction of patients in each cluster changed during treatment, no new TME clusters emerged as treatment progressed. These clusters were associated with progression free survival (PFS) (p-Val = 0.020) and overall survival (OS) (p-Val = 0.067) when measured in pre-transplant samples. The most striking outcomes were represented by Cluster 5 (N = 106) characterized by a low innate to adaptive cell ratio and shortened patient survival (Figure 1, 2). This cluster had worse outcomes than others (estimated mean PFS = 58 months compared to 71+ months for other clusters, p-Val = 0.002; estimate mean OS = 105 months compared with 113+ months for other clusters, p-Val = 0.040). Compared to other immune clusters, the adaptive-skewed TME of Cluster 5 is characterized by low granulocyte populations and high antigen-presenting, CD8 T, and B cell populations. As might be expected, this cluster was also significantly enriched for ISS3 and GEP70 high risk patients, as well as Del1p, Del1q, t12;14, and t14:16. Importantly, this TME persisted even when the induction therapy significantly reduced the tumor load (Table 1). At post-induction, outcomes for the 69 / 245 patients in Cluster 5 remain significantly worse (estimate mean PFS = 56 months compared to 71+ months for other clusters, p-Val = 0.004; estimate mean OS = 100 months compared to 121+ months for other clusters, p-Val = 0.002). The analysis of on-treatment samples showed that the number of patients in Cluster 5 decreases from 30% before treatment to 12% after transplant, and of the 63 patients for whom we have both pre-treatment and post-transplant samples, 18/20 of the Cluster 5 patients moved into other immune clusters; 13 into Cluster 4. The non-5 clusters (with better PFS and OS overall) had higher amounts of granulocytes and lower amounts of CD8 T cells. Some clusters (1 and 4) had increased natural killer (NK) cells and decreased dendritic cells, while other clusters (2 and 3) had increased adipocytes and increases in M2 macrophages (Cluster 2) or NK cells (Cluster 3). Taken together, the gain of granulocytes and adipocytes was associated with improved outcome, while increases in the adaptive immune compartment was associated with poorer outcome. Conclusions We identified distinct clusters of patient TMEs from bulk transcriptome profiles by computationally estimating the CD138- fraction of TMEs. Our findings identified differential immune and stromal compositions in patient clusters with opposing clinical outcomes and tracked membership in those clusters during treatment. Adding this layer of TME to the analysis of myeloma patient baseline and on-treatment samples enables us to formulate biological hypotheses and may eventually guide therapeutic interventions to improve outcomes for patients. Disclosures Danziger: Celgene Corporation: Employment, Equity Ownership. McConnell:Celgene Corporation: Employment. Gockley:Celgene Corporation: Employment. Young:Celgene Corporation: Employment, Equity Ownership. Schmitz:Celgene Corporation: Employment, Equity Ownership. Reiss:Celgene Corporation: Employment, Equity Ownership. Davies:MMRF: Honoraria; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; TRM Oncology: Honoraria; Abbvie: Consultancy; ASH: Honoraria; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria. Copeland:Celgene Corporation: Employment, Equity Ownership. Fox:Celgene Corporation: Employment, Equity Ownership. Fitch:Celgene Corporation: Employment, Equity Ownership. Newhall:Celgene Corporation: Employment, Equity Ownership. Barlogie:Celgene: Consultancy, Research Funding; Dana Farber Cancer Institute: Other: travel stipend; Multiple Myeloma Research Foundation: Other: travel stipend; International Workshop on Waldenström's Macroglobulinemia: Other: travel stipend; Millenium: Consultancy, Research Funding; European School of Haematology- International Conference on Multiple Myeloma: Other: travel stipend; ComtecMed- World Congress on Controversies in Hematology: Other: travel stipend; Myeloma Health, LLC: Patents & Royalties: : Co-inventor of patents and patent applications related to use of GEP in cancer medicine licensed to Myeloma Health, LLC. Trotter:Celgene Research SL (Spain), part of Celgene Corporation: Employment, Equity Ownership. Hershberg:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Dervan:Celgene Corporation: Employment, Equity Ownership. Ratushny:Celgene Corporation: Employment, Equity Ownership. Morgan:Takeda: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Research Funding.

Introduction: Chromothripsis and chromoplexy are gross structural events that deregulate multiple genes simultaneously and may help explain rapid changes in clinical behavior. Previous screening studies in multiple myeloma (MM) using copy number arrays have identified chromothripsis at a low frequency (1.3%) and suggested it adversely impacts prognosis. Here, using whole genome sequencing (WGS) data we have identified a higher frequency of these events, suggesting they are more common than previously thought. Methods: 10X ChromiumWGS (10XWGS) from 76 newly diagnosed MM (NDMM) patients were analyzed for structural rearrangements using Longranger. Oxford Nanopore long read sequencing was performed on 2 samples. Long insert WGS data from 813 NDMM patient samples from the Myeloma Genome Project (MGP) were analyzed for structural rearrangements using Manta. Whole exome sequencing was available for 712 samples. RNA-seq was available for 643 samples. Chromothripsis was determined by manual curation of breakpoint and copy number data. Chromoplexy was defined as rearrangements within 1 Mb of one another involving 3 or more chromosomes. Results: Chromoplexy was detected in 33/76 (46%) cases using 10XWGS data, and cross validated in the MGP WGS dataset being found in 30% (247/813) of samples and was most frequent on chromosomes 8 (11.7% of samples), 14 (10.6%), 11 (9.6%), 1 (9.5%), 6 (8.0%), 22 (7.6%), 12 (6.7%), and 17 (6.7%). The gene regions most involved in chromoplexy events were MYC (chr8; 7.3%), IGH (chr14, 8.8%), IGL (chr22; 4.6%), CCND1 (chr11; 3.9%), TXNDC5 (chr6; 1.7%), FCHSD2 (chr11; 1.4%), FAM46C (chr1; 1.2%), MMSET (chr4; 1.2%), and MAP3K14 (chr17; 0.7%). Chromoplexy samples involved pairings of super-enhancer donors (IGH, IGL, FAM46C, TXNDC5) and oncogenic receptors (CCND1, MMSET, MAP3K14, MYC) implicating transcriptional deregulation. To confirm, RNASeq showed an elevation of expression over median in the oncogenic receptors when paired with a donor: CCND1 (median expression = 12.0 vs. median expression with donor = 17.9), MAP3K14 (10.8 vs. 14.7), MYC (12.7 vs. 14.1) and MMSET (11.9 vs. 16.7). We also identified elevated expression of PAX5 (8.23 vs. 13.79) and two cases where BCL2 (13.32 vs. 14.68) partnered with MYC, one involved IGH similar to follicular lymphoma. To determine if chromoplexy events were happening on the same allele, we performed long read sequencing using Oxford Nanopore on a sample with a t(2;6;8;11) event. We observed a read mapped to chromosome 2, with secondary alignment to chromosomes 6 and 8. This single 32 kb read was a continuous t(2;6;8) event, proving these events occurred on the same allele. However, despite close proximity, the data did not put the t(8;11) in the same read meaning this event occurred on a different allele or sub-clone, suggesting ongoing genomic instability. Chromothripsis was detected in 16/76 (21%) cases using 10XWGS, and was consistent in MGP data, (170/813; 21%). Chromothripsis occurred on all chromosomes but at different frequencies where chromosome 1 had most events (5.1%), followed by 14 (2.4%), 11 (2.3%), 12 (2.2%), 20 (1.9%), 17 (1.9%), and 8 (1.9%). We hypothesized the presence of both chromoplexy and chromothripsis could be associated with ineffective DNA repair and indeed, using WES data, patients with both events show more mutations in TP53 (19% vs. 5%) and ATM (10% vs. 4%) implicating homologous recombination deficiency as an etiologic mechanism. Gene set enrichment analysis showed significant enrichment and positive normalized enrichment score (NES) for the DNA Repair (P = 0.01; NES = 1.7) and MYC pathways (P = 0.01; NES = 3.2) consistent with previous results. In relation to prognosis, chromoplexy and chromothripsis have a negative impact on progression free survival (28.6 months vs. 42.8 months, P=0.03 and 28.6 months vs. 40.7 months P=0.01, respectively). When patients with both chromoplexy and chromothripsis (9%) were examined there was a pronounced effect on PFS (40.7 months vs. 22.7 months, P Conclusion: Complex structural events are seen frequently in MM and could help explain disease progression. Severe cases with both chromoplexy and chromothripsis are associated with acquired genomic instability and an adverse impact on prognosis either directly or due to their association with DNA repair abnormalities. This opens the possibility of specifically therapeutically targeting the underlying DNA abnormalities. Disclosures Flynt: Celgene Corporation: Employment, Equity Ownership. Ortiz:Celgene Research SL (Spain), part of Celgene Corporation: Employment, Equity Ownership. Dervan:Celgene Corporation: Employment, Equity Ownership. Gockley:Celgene Corporation: Employment. Davies:Janssen: Consultancy, Honoraria; TRM Oncology: Honoraria; Abbvie: Consultancy; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; ASH: Honoraria; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; MMRF: Honoraria; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees. Thakurta:Celgene Corporation: Employment, Equity Ownership. Morgan:Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Janssen: Research Funding.

Introduction The multistep progression of multiple myeloma from a normal plasma cell to a system with the features of invasive cancer provides a unique opportunity to understand the co-evolution of the malignant clone within its microenvironment. Understanding these changes is becoming increasingly important as we attempt to design early intervention strategies and to precisely leverage emerging immunotherapeutic modalities to prevent and treat disease progression. In this work, we used mass cytometry (CyTOF) to generate a high-resolution map of the BM microenvironment and how it changes during the transition from health through pre-malignancy to disease. This approach allows us to both understand microenvironmental patterns that correlate with rapid disease progression as well as to generate new hypotheses about permissive and protective immune-phenotypes that might reveal novel immunologic drug targets. Methods To understand the immunologic characteristics of monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), newly diagnosed multiple myeloma (NDMM) and relapsed-refractory multiple myeloma (RRMM), we profiled BM aspirates from 79 patients using mass cytometry by time of flight (CyTOF). Furthermore, we compared the BM compartment of pre-malignant, malignant, and relapsed disease states to the BM of healthy donors using a 37-marker pan-immune panel. In this panel, we used antibodies against several immune lineages, tumor antigens, and functional surface markers, including co-stimulatory and co-inhibitory receptors. Cell clusters defined by Citrus analysis of CyTOF data were combined into an evolutionarily optimized decision tree by evtree to identify cluster interactions that strongly partition patient samples. Results During MGUS, when the tumor plasma cells are Conclusions Immune dysregulation is thought to be a major contributor to the progression and outcome of patients with MGUS, SMM, and MM. Using CyTOF, we have begun to benchmark the content of the immune microenvironment across the myeloma continuum. Based on this cross-sectional analysis we hypothesize that it is important to further interrogate whether the losses in the CD4 memory and effector populations we described correlate with outcomes after therapy with either CAR T or T cell engager trials that are currently ongoing, and whether reconstituting these cell types could provide a meaningful treatment strategy. Disclosures Young: Celgene Corporation: Employment, Equity Ownership. Danziger:Celgene Corporation: Employment, Equity Ownership. Fitch:Celgene Corporation: Employment, Equity Ownership. Schmitz:Celgene Corporation: Employment, Equity Ownership. Gockley:Celgene Corporation: Employment. McConnell:Celgene Corporation: Employment. Reiss:Celgene Corporation: Employment, Equity Ownership. Copeland:Celgene Corporation: Employment, Equity Ownership. Newhall:Celgene Corporation: Employment, Equity Ownership. Hershberg:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Foy:Celgene Corporation: Employment, Equity Ownership. Ratushny:Celgene Corporation: Employment, Equity Ownership. Dervan:Celgene Corporation: Employment, Equity Ownership. Morgan:Takeda: Consultancy, Honoraria; Janssen: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria.

Summary Autism spectrum disorder (ASD) is a complex developmental syndrome of unknown etiology. Recent studies employing exome- and genome-wide sequencing have identified nine high-confidence ASD (hcASD) genes. Working from the hypothesis that ASD-associated mutations in these biologically pleiotropic genes will disrupt intersecting developmental processes to contribute to a common phenotype, we have attempted to identify time periods, brain regions, and cell types in which these genes converge. We have constructed coexpression networks based on the hcASD "seed" genes, leveraging a rich expression data set encompassing multiple human brain regions across human development and into adulthood. By assessing enrichment of an independent set of probable ASD (pASD) genes, derived from the same sequencing studies, we demonstrate a key point of convergence in midfetal layer 5/6 cortical projection neurons. This approach informs when, where, and in what cell types mutations in these specific genes may be productively studied to clarify ASD pathophysiology.

Background A 4:1 male to female sex bias has consistently been observed in autism spectrum disorder (ASD). Epidemiological and genetic studies suggest a female protective effect (FPE) may account for part of this bias; however, the mechanism of such protection is unknown. Quantitative assessment of ASD symptoms using the Social Responsiveness Scale (SRS) shows a bimodal distribution unique to females in multiplex families. This leads to the hypothesis that a single, common genetic locus on chromosome X might mediate the FPE and produce the ASD sex bias. Such a locus would represent a major therapeutic target and is likely to have been missed by conventional genome-wide association study (GWAS) analysis. Methods To explore this possibility, we performed an association study in affected versus unaffected females, considering three tiers of single nucleotide polymorphisms (SNPs) as follows: 1) regions of chromosome X that escape X-inactivation, 2) all of chromosome X, and 3) genome-wide. Results No evidence of a SNP meeting the criteria for a single FPE locus was observed, despite the analysis being well powered to detect this effect. Conclusions The results do not support the hypothesis that the FPE is mediated by a single genetic locus; however, this does not exclude the possibility of multiple genetic loci playing a role in the FPE. Electronic supplementary material The online version of this article (doi:10.1186/s13229-015-0014-3) contains supplementary material, which is available to authorized users.