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Purpose: Clinical patterns and the associated optimal management of acquired resistance to PD-(L)1 blockade are poorly understood. Experimental Design: All cases of metastatic lung cancer treated with PD-(L)1 blockade at Memorial Sloan Kettering were reviewed. In acquired resistance (complete/partial response per RECIST, followed by progression), clinical patterns were distinguished as oligo (OligoAR ≤ 3 lesions of disease progression) or systemic (sAR). We analyzed the relationships between patient characteristics, burden/location of disease, outcomes, and efficacy of therapeutic interventions. Results: Of 1,536 patients, 312 (20%) had an initial response and 143 developed AR (9% overall, 46% of responders). OligoAR was the most common pattern (80/143, 56%). Baseline tumor mutational burden, depth of response, and duration of response were significantly increased in oligoAR compared with sAR (P < 0.001, P = 0.03, P = 0.04, respectively), whereas baseline PD-L1 and tumor burden were similar. Post-progression, oligoAR was associated with improved overall survival (median 28 months vs. 10 months, P < 0.001) compared with sAR. Within oligoAR, post-progression survival was greater among patients treated with locally-directed therapy (e.g., radiation, surgery; HR, 0.41; P = 0.039). Fifty-eight percent of patients with oligoAR treated with locally-directed therapy alone are progression-free at last follow-up (median 16 months), including 13 patients who are progression-free more than 2 years after local therapy. Conclusions: OligoAR is a common and distinct pattern of acquired resistance to PD-(L)1 blockade compared with sAR. OligoAR is associated with improved post-progression survival and some cases can be effectively managed with local therapies with durable benefit.

Cancer immunoediting1is a hallmark of cancer2that predicts that lymphocytes kill more immunogenic cancer cells to cause less immunogenic clones to dominate a population. Although proven in mice1,3, whether immunoediting occurs naturally in human cancers remains unclear. Here, to address this, we investigate how 70 human pancreatic cancers evolved over 10 years. We find that, despite having more time to accumulate mutations, rare long-term survivors of pancreatic cancer who have stronger T cell activity in primary tumours develop genetically less heterogeneous recurrent tumours with fewer immunogenic mutations (neoantigens). To quantify whether immunoediting underlies these observations, we infer that a neoantigen is immunogenic (high-quality) by two features—‘non-selfness’ based on neoantigen similarity to known antigens4,5, and ‘selfness’ based on the antigenic distance required for a neoantigen to differentially bind to the MHC or activate a T cell compared with its wild-type peptide. Using these features, we estimate cancer clone fitness as the aggregate cost of T cells recognizing high-quality neoantigens offset by gains from oncogenic mutations. With this model, we predict the clonal evolution of tumours to reveal that long-term survivors of pancreatic cancer develop recurrent tumours with fewer high-quality neoantigens. Thus, we submit evidence that that the human immune system naturally edits neoantigens. Furthermore, we present a model to predict how immune pressure induces cancer cell populations to evolve over time. More broadly, our results argue that the immune system fundamentally surveils host genetic changes to suppress cancer.

Retrotransposons are genetic elements that have the ability to copy and paste themselves in the genome via the proteins they encode. Since the rapid growth of a retrotransposon can be highly deleterious at the organismal level, many of these genetic parasites are suppressed or have been inactivated over evolutionary time. However, the human genome still hosts the active retrotransposon LINE-1, whose aberrant expression is associated with various diseases, especially epithelial cancers. Despite these associations, a quantitative understanding of the dynamics and diversity of LINE-1 insertions in somatic tissue is lacking. In order to address this gap, we present a population dynamic model of LINE-1 retrotransposition in individual cells. Using the model, we show that at demographic equilibrium, the LINE-1 copy number distribution is broader than would be expected from classical population genetic models. We demonstrate how this broadening distorts the frequency spectrum of insertions. We compare the model's predictions to data from whole genome sequencing of individual tumor cells. Citation Format: Stephen Martis, Alexander Solovyov, Jayon Lihm, Hao Li, Benjamin Greenbaum. The dynamics of LINE-1 retrotransposition in cellular populations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 860.

As tumors evolve, cancer cells acquire somatic mutations and these mutations generate tumor specific neoantigens that are different from self and can be recognized by T-cells, inducing anti-tumor immune responses. Such immunogenic antigens can be effective targets for neoantigen-based cancer vaccines. However, the identification of immunogenic neoantigens remains limited with the current prediction models. Here we designed mouse experiments to model tumor evolution under immune pressure and its association with T-cell clones to identify these antigens agnostically and improve current prediction models. We injected three lung cancer cell lines (KPA, KPC, and HKP1) in wildtype immune-competent C57BL/6 mice and immune-deficient Rag1 defective (Rag1 KO) mice, respectively. The three tumor cell lines have common driver mutations, Kras G12D/+ and p53 flox/flox. Two weeks post tumor implantation, whole exome sequencing and RNA-seq was performed on tumor samples. We also performed T cell receptor (TCR) sequencing to profile tumor infiltrated TCR clones. Despite the shared driver mutations, tumor growth patterns in vivo over time are very distinct for each cell line. Interestingly, KPA tumors show differential evolutionary patterns in wild type mice versus Rag1 KO mice, regressing in the former but rapidly progressing in the latter, suggesting that the difference can be attributed to immunoediting of KPA specific neoantigens. HKP1 tumors do not show substantial differences in that aggressive tumor progression is observed in both types of mice. Using WES data, we estimated the cancer cell fraction of each mutation based on phylogeny re-construction. We found that evolved KPA tumors (immunogenic) had significantly lower mutation burden in wild type mice compared to Rag1 KO mice (3410 vs 4199 on average), and the fraction of cell line mutations edited in vivo is significantly higher in wild type than in Rag1 KO (26% vs 14% on average), suggesting again the active on-going immunosurveillance in immune competent mice. In contrast, HKP1 tumors (non-immunogenic) do not show significant differences in mutation burden nor fraction of mutations edited between wild type and Rag1 KO mice. Furthermore, TCR-seq data show that the clonal expansion of T-cells is strongly associated with tumor immunogenicity. KPA tumor samples show significantly higher TCR clustering but with less diversity, quantified by modified Simpson’s Index, that is strongly correlated with the suppression of mutational burden (r=0.74). In summary, we found that tumor evolution in immune competent mice is dependent on mutational context of the tumor. By analyzing longitudinal tumor and TCR sequencing data, we showed that the immunogenicity of tumors is associated with significant decrease in mutational burden and higher T-cell clustering that is indicative of tumor mutation and TCR clone expansion co-evolution in immune competent mice. Citation Format: Jayon Lihm, Hyejin Choi, Mariam M. George, Yuval Elhanati, David Hoyos, Marta Luksza, Taha Merghoub, Benjamin D. Greenbaum. Modeling tumor immunoediting coupled with T-cell repertoire dynamic [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 610.

659 Background: Combination therapy with I/N can achieve long-term benefit in a sizable proportion of RCC pts, but broad application has been challenged by a high incidence of irAEs. Host features affecting antigen presentation are candidate determinants of irAE pathogenesis, and isolated reports have linked Human Leukocyte Antigen (HLA) variations to organ- specific irAEs. We analyzed data for pts treated on a phase 3 trial to investigate association of class 1 HLA variants with development of irAEs from I/N and develop a tool to predict risk for toxicity. Methods: We analyzed germline HLA + clinical data for 472 pts receiving I/N vs sunitinib (SUT). Based on allelic variants for HLA-A and B pts were categorized into 12 established HLA "Super-Types" (ST), sets of HLA variants with largely overlapping peptide binding specificity. We conducted uni- and multivariate (UV; MV) Cox proportional hazards regression to correlate HLA-ST variables with time to treatment-related AEs (TTrAE, grade 2+) in I/N pts using the Kaplan Meier method. Several MV HLA-ST models were developed on a discovery set (DISC; 2/3 random sample of I/N pts without replacement ) and compared using model concordance (c-index) on a validation set (VAL; remaining 1/3). Model coefficients were used to create a “HLA-ST score” that could be computed for individual pts. Results: 235 pts and 237 pts received I/N vs SUT and had available HLA data, respectively. On UV analysis for I/N, HLA-B07 ST had protective association TTrAE (HR= 0.65, 95% CI: 0.46,0.90; p= 0.010), while B62 associated adversely (HR=1.64, 95% CI: 1.12, 2.40; p=0.014). Relevant to the development of our model we identified interactions between several pairs of HLA ST. The HLA ST model with best performance in DISC (c-index= 0.606) and VAL (c-index=0.595) integrates B07, B62, A01, B08, and two interactions: B07-B08 and B07-A01. The model-generated HLA-ST score was significantly associated with TTrAE after adjusting for race, BMI, region, PDL1 status, and MSKCC risk score (DISC p= vs < median had significantly different TTrAE both in DISC (p=0.004) and VAL (p=0.009); again, no difference was observed in the SUT arm (p=0.5). The weighted HLA-ST score had no association with PFS or OS for I/N pts. Conclusions: In this large sample of I/N-treated patients, class I HLA variants were associated with the risk of developing irAEs. We developed a HLA ST based score that correlated with treatment toxicity independent of relevant clinical and demographic features. No association with TTrAE was seen in SUT-treated pts. These results highlight the potential of characterizing germline features to predict immune related toxicity upfront and deserves further study. Clinical trial information: NCT02231749 .

Although cancer immunotherapy with PD-(L)1 blockade is now routine treatment for patients with lung cancer, remarkably little is known about acquired resistance. We examined 1,201 patients with NSCLC treated with PD-(L)1 blockade to clinically characterize acquired resistance, finding it to be common (occurring in more than 60% of initial responders), with persistent but diminishing risk over time, and with distinct metastatic and survival patterns compared to primary resistance. To examine the molecular phenotype and potential mechanisms of acquired resistance, we performed whole transcriptome and exome tumor profiling in a subset of NSCLC patients (n=29) with acquired resistance. Systematic immunogenomic analysis revealed that tumors with acquired resistance generally had enriched signals of inflammation (including IFNγ signaling and inferred CD8+ T cells) and could be separated into IFNγ upregulated and stable subsets. IFNγ upregulated tumors had putative routes of resistance with signatures of dysfunctional interferon signaling and mutations in antigen presentation genes. Transcriptomic profiling of cancer cells from a murine model of acquired resistance to PD-(L)1 blockade also showed evidence of dysfunctional interferon signaling and acquired insensitivity to in vitro interferon gamma treatment. In summary, we characterized clinical and molecular features of acquired resistance to PD-(L)1 blockade in NSCLC and found evidence of ongoing but dysfunctional IFN response. The persistently inflamed, rather than excluded or deserted, tumor microenvironment of acquired resistance informs therapeutic strategies to effectively reprogram and reverse acquired resistance.

4584 Background: We previously reported the clinical outcomes of a positive multi-center phase II trial of neoadjuvant gemcitabine (G) and cisplatin (C) plus atezolizumab (A) in patients with muscle-invasive bladder cancer (Funt, et al. JCO 2022). In this and another trial of neoadjuvant GC with pembrolizumab (Rose et al, JCO 2021), PD-L1 positivity by immunohistochemistry was not predictive of non–muscle-invasive downstaging ( < pT2N0). Therefore, we investigated other pre-treatment tissue-based genomic and gene expression biomarkers of response and resistance. Methods: 36 pts had pre-treatment tissue available for genomic analysis. We performed targeted hybridization capture DNA sequencing using the CLIA-certified MSK-IMPACT platform and whole transcriptome RNA sequencing. We examined genomic and gene expression biomarkers which have been previously investigated in the context of neoadjuvant cisplatin-based chemotherapy or anti-PD-1/L1 immunotherapy for MIBC, including tumor mutation burden (TMB), a DNA damage response (DDR) 9-gene panel (NCT03609216) associated with response to neoadjuvant chemotherapy, and an 8-gene cytotoxic T cell transcriptional signature associated with response to neoadjuvant A (tGE8; Powles et al, Nature Medicine 2019). We also evaluated TGF-β pathway activation, which was associated with resistance to A in pts with metastatic BC (Mariathasan et al, Nature 2018). Putative biomarkers were assessed for correlation with < pT2N0, the trial’s primary endpoint. Results: DNA was available from all 36 pts, and RNA met quality control metrics for 29 pts. TMB was significantly higher in pts with < pT2N0 (median 16 mut/Mb, IQR 12-25) versus ≥ pT2N0 (median 10 mut/ Mb, IQR 8-10; p < 0.01). A single patient had a TMB > 200 Mut/Mb with a POLE hotspot mutation and achieved pT0N0; TMB was still significantly higher in responders after omission of this patient (p < 0.01). Nine of 25 pts (36%) with < pT2N0 had a deleterious DDR mutation versus 1 of 10 pts (10%) with ≥ pT2N0 (p = 0.13). While tGE8 was significantly increased in patients with < pT2N0 compared to those without (p = 0.01), TGF-β pathway activation was not increased in pts with ≥ pT2N0 (p = 0.99). Conclusions: TMB and the tGE8 cytotoxic T cell transcriptional signature were associated with response to combination GC+A in muscle-invasive bladder cancer. More detailed molecular analyses will be reported. Clinical trial information: NCT02989584.

Cancer immunoediting is a hallmark of cancer that predicts T cells recognize and kill tumor cells expressing immunogenic mutations (neoantigens), to induce less immunogenic clones to outgrow in tumors. Although established through longitudinal studies of how tumors evolve in immune-proficient and -deficient mice, whether the human immune system naturally targets neoantigens to edit tumors remains unclear. Here, we investigate how 70 human pancreatic ductal adenocarcinomas (PDACs) – a poorly immunogenic cancer with few neoantigens and thus largely presumed to not be subject to immunoediting – evolved over 10 years. We use longitudinal tumor sampling to compare how primary tumors evolve to recurrence in rare long-term PDAC survivors previously shown to have more immunogenic tumors (n = 9 patients, n = 9 primary and 22 recurrent tumors, median survival 5.4 years), to short-term survivors with less immunogenic primary tumors (n = 6 patients, n = 6 primary and 33 recurrent tumors, median survival 1.8 years). Compared to short-term survivors, we observe that long-term survivors evolve fewer recurrent tumors with longer latency, and distinct tissue tropism. To evaluate if differential immune pressures could explain these differences, we perform whole exome sequencing to bioinformatically predict tumor clonal structures and neoantigens. We discover that despite longer times to evolve, long-term survivors evolve genetically less heterogeneous tumors with fewer clones, fewer nonsynonymous mutations, and fewer neoantigens. To identify the edited neoantigens, we sought to improve upon and apply our previously defined quality model that quantifies the immunogenic features of a neoantigen. With our quality model, we now infer a neoantigen is immunogenic (“high quality”) by two parameters – if the immune system can recognize a neoantigen as “non-self” by its similarity to known immunogenic antigens, and discriminate it from “self” by estimating if a neoantigen has sufficient antigenic distance from its wild-type peptide to differentially bind the MHC or activate a T cell. We integrate these features to estimate neoantigen quality in primary and recurrent tumors of long- and short-term survivors. With the quality model, we observe that neoantigens with greater antigenic distance (“less self”) are more depleted in primary and recurrent tumors of long- compared to short-term survivors. Furthermore, we find that long-term survivors evolve markedly fewer new neoantigens of strikingly lower quality, to indicate clones with high quality (more immunogenic) neoantigens are immunoedited. Thus, we submit longitudinal evidence that the human immune system naturally edits neoantigens in PDAC. Furthermore, we present a model that describes how cancer neoantigens evolve under immune pressure over time, with implications for cancer biology and therapy. More broadly, our results argue that immunoediting is a fundamental cancer suppressive mechanism that can be quantified to predict tumor evolution. Citation Format: Luis A. Rojas, Marta Łuksza, Zachary M. Sethna, Kevin Soares, Joanne Leung, Jayon Lihm, David Hoyos, Anton Dobrin, Rajya Kappagantula, Alvin Makohon-Moore, Amber Johns, Anthony Gill, Masataka Amisaki, Pablo Guasp, Abderezak Zebboudj, Rebecca Yu, Adrienne Kaya Chandra, Zagaa Odgerel, Michel Sadelain, Erin Patterson, Christine Iacobuzio-Donahue, Benjamin D. Greenbaum, Vinod P. Balachandran. High quality neoantigens are immunoedited in long-term pancreatic cancer survivors [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PR-003.

BackgroundCancer immunoediting predicts that T cells selectively kill tumor cells expressing immunogenic mutations (neoantigens) resulting in less immunogenic clones to outgrow in tumors.1 Although established through longitudinal studies of how tumors evolve in immune-proficient and -deficient mice,1 2 whether the human immune system naturally targets neoantigens to edit tumors, and the principles that identify the edited neoantigens, remains unclear.MethodsTo investigate if immune selective pressures on neoantigens alter how human tumors evolve, we longitudinally studied how 70 human pancreatic ductal adenocarcinomas (PDACs) - a poorly immunogenic cancer largely presumed to not be subject to immunoediting - evolved over 10 years. We use exome sequencing, neoantigen identification, and clonal reconstruction to compare how primary PDACs evolve to recurrence in rare long-term PDAC survivors previously shown to have more immunogenic tumors3 (n = 9 patients, n = 9 primary, 22 recurrent tumors), to short-term survivors with less immunogenic primary tumors (n = 6 patients, n = 6 primary, 33 recurrent tumors). To identify immunogenic “high quality” neoantigens, we use neopeptide-T cell functional assays and computational modeling to extend and apply a previously developed neoantigen quality model3 4 by predicting high quality neoantigens as arising from amino acid substitutions with sufficient antigenic distance from cognate wild-type peptides to differentially bind the MHC or activate a T cell.ResultsCompared to short-term survivors, we observe that long-term survivors evolve fewer recurrent tumors with longer latency, and distinct tissue tropism. To evaluate if differential immune pressures explained these differences, we discover that despite longer times to evolve, long-term survivors evolve genetically less heterogeneous tumors with fewer clones, fewer nonsynonymous mutations, and fewer neoantigens. To identify if high quality neoantigens are selectively edited in recurrent tumors of long-term survivors, we observe that neoantigens with greater antigenic distance (“less self”) are more depleted in primary and recurrent tumors of long- compared to short-term survivors. Furthermore, we find that long-term survivors evolve markedly fewer new neoantigens of strikingly lower quality, to indicate clones with high quality neoantigens are immunoedited.ConclusionsWe submit longitudinal evidence that the human immune system naturally edits neoantigens in PDAC. Furthermore, we present a model that describes how cancer neoantigens evolve under immune pressure over time, with implications for cancer biology and therapy. More broadly, our results argue that immunoediting is a fundamental cancer suppressive mechanism that can be quantified to predict tumor evolution.AcknowledgementsThis work was supported by NIH U01 CA224175 (V.P.B), a Stand Up to Cancer Convergence Award (B.D.G, V.P.B.), a Damon Runyon Clinical Investigator Award (V.P.B), and the Avner Pancreatic Cancer Foundation (A.J, A.G). Services by the Integrated Genomics Core were funded by the NCI Cancer Center Support Grant (P30 CA08748), Cycle for Survival, and the Marie-Josée and Henry R. Kravis Center for Molecular Oncology.ReferencesShankaran V, et al. IFNgamma and lymphocytes prevent primary tumour development and shape tumour immunogenicity. Nature 2001;410:1107–1111.Matsushita H, et al. Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature 2012;482:400–404.Balachandran VP, et al. Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer. Nature 2017;551:512–516.Łuksza M, et al. A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy. Nature 2017;551:517–520.Ethics ApprovalThis study was performed in strict compliance with all institutional ethical regulations and approved by the institutional review boards of Memorial Sloan Kettering Cancer Center (MSK), the Garvan Institute of Medical Research, and the The Johns Hopkins Hospital (JHH). We obtained informed consent from all patients.

Cancer immunoediting, a hallmark of cancer, predicts that lymphocytes recognize tumor-specific mutations (neoantigens) to kill immunogenic tumor cells and select less immunogenic clones to survive in immunocompetent hosts. Yet, though proven in mice, whether immunoediting governs how human tumors evolve naturally, and the principles of how the immune system edits tumors remain unclear. Here, we report that T cell rich tumors of rare long-term survivors of human pancreatic ductal adenocarcinoma longitudinally lose immunogenic features predicted by a fitness model based on immune recognition of high quality neoantigens. We find that compared to T cell poor tumors in short-term survivors, long-term survivors evolve less immunogenic recurrent tumors over 10 years with fewer clones, fewer neoantigens, and new neoantigens of markedly lower quality, to indicate that the immune system edits lower fitness clones with high-quality neoantigens. To explore if the immune system more broadly selects against non-self-like changes in host genomes, we define a minimal amino acid substitution distance sufficient for T cell receptors to discriminate self from non-self mutations. We find that both primary and recurrent tumors in long but not short-term survivors are enriched in self-like mutations, to suggest that the immune system depletes non-self-like mutations. Thus, we submit longitudinal evidence that the immune system edits neoantigens to sculpt recurrent human pancreatic ductal adenocarcinomas, a lethal tumor largely considered resistant to endogenous immune attack. Furthermore, we demonstrate that the neoantigen quality fitness model predicts how immune pressure changes tumor cell populations over time, with significant implications for cancer biology and immunotherapy. More broadly, our results argue that cancer immunoediting is a fundamental principle of how human cancers evolve in immunocompetent hosts. Citation Format: Marta Luksza, Zachary Sethna, Luis Rojas, Kevin Soares, Yuval Elhanati, Jayon Lihm, David Hoyos, Rajya Kappagantula, Alvin M. Moore, Erin Patterson, Christine Iacobuzio-Donahue, Benjamin Greenbaum, Vinod P. Balachandran. High quality neoantigens are immunoedited in long term survivors of pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB005.

Chromatin accessibility provides an important window into the regulation of gene expression. Recently, the Assay of Transposase Accessible Chromatin with sequencing (ATAC-seq) was developed to profile genome-wide chromatin accessibility. In this work we analyzed 193 ATAC-seq samples from 12 studies to determine the robustness of peaks, as well as their specificity across studies. We employ a read-downsampling approach and find that even samples which have high average read-depth yield poorly powered peaks using conventional pipelines. Finding that many peaks are sensitive to slight perturbations in read-sampling, we develop an approach to improve the robustness of peak signals and apply this novel method to detect differential accessibility between the amygdala and cortex. Most peak calling results heavily and unreasonably depend on the absolute number of reads, easily yielding artifacts when differential peak evaluations are performed. These problems can be ameliorated by resampling reads to determine the robust aggregate result.

Psychiatric disorders are a group of genetically related diseases with highly polygenic architectures. Genome-wide association analyses have made substantial progress towards understanding the genetic architecture of these disorders. More recently, exome- and whole-genome sequencing of cases and families have identified rare, high penetrant variants that provide direct functional insight. There remains, however, a gap in the heritability explained by these complementary approaches. To understand how multiple genetic variants combine to modify both severity and penetrance of a highly penetrant variant, we sequenced 48 whole genomes from a family with a high loading of psychiatric disorder linked to a balanced chromosomal translocation. The (1;11)(q42;q14.3) translocation directly disrupts three genes: DISC1, DISC2, DISC1FP and has been linked to multiple brain imaging and neurocognitive outcomes in the family. Using DNA sequence-level linkage analysis, functional annotation and population-based association, we identified common and rare variants in GRM5 (minor allele frequency (MAF) > 0.05), PDE4D (MAF > 0.2) and CNTN5 (MAF

Schizophrenia (SCZ), bipolar disorder (BD) and recurrent major depressive disorder (rMDD) are common psychiatric illnesses. All have been associated with lower cognitive ability, and show evidence of genetic overlap and substantial evidence of pleiotropy with cognitive function and neuroticism. Disrupted in schizophrenia 1 (DISC1) protein directly interacts with a large set of proteins (DISC1 Interactome) that are involved in brain development and signaling. Modulation of DISC1 expression alters the expression of a circumscribed set of genes (DISC1 Regulome) that are also implicated in brain biology and disorder. Here we report targeted sequencing of 59 DISC1 Interactome genes and 154 Regulome genes in 654 psychiatric patients and 889 cognitively-phenotyped control subjects, on whom we previously reported evidence for trait association from complete sequencing of the DISC1 locus. Burden analyses of rare and singleton variants predicted to be damaging were performed for psychiatric disorders, cognitive variables and personality traits. The DISC1 Interactome and Regulome showed differential association across the phenotypes tested. After family-wise error correction across all traits (FWERacross), an increased burden of singleton disruptive variants in the Regulome was associated with SCZ (FWERacross P=0.0339). The burden of singleton disruptive variants in the DISC1 Interactome was associated with low cognitive ability at age 11 (FWERacross P=0.0043). These results identify altered regulation of schizophrenia candidate genes by DISC1 and its core Interactome as an alternate pathway for schizophrenia risk, consistent with the emerging effects of rare copy number variants associated with intellectual disability.

Schizophrenia is a serious psychiatric disorder with a broadly undiscovered genetic etiology. Recent studies of de novo mutations (DNMs) in schizophrenia and autism have reinforced the hypothesis that rare genetic variation contributes to risk. We carried out exome sequencing on 57 trios with sporadic or familial schizophrenia. In sporadic trios, we observed a ~3.5-fold increase in the proportion of nonsense DNMs (0.101 vs 0.031, empirical P=0.01, Benjamini-Hochberg-corrected P=0.044). These mutations were significantly more likely to occur in genes with highly ranked probabilities of haploinsufficiency (P=0.0029, corrected P=0.006). DNMs of potential functional consequence were also found to occur in genes predicted to be less tolerant to rare variation (P=2.01 × 10(-)(5), corrected P=2.1 × 10(-)(3)). Genes with DNMs overlapped with genes implicated in autism (for example, AUTS2, CHD8 and MECP2) and intellectual disability (for example, HUWE1 and TRAPPC9), supporting a shared genetic etiology between these disorders. Functionally CHD8, MECP2 and HUWE1 converge on epigenetic regulation of transcription suggesting that this may be an important risk mechanism. Our results were consistent in an analysis of additional exome-based sequencing studies of other neurodevelopmental disorders. These findings suggest that perturbations in genes, which function in the epigenetic regulation of brain development and cognition, could have a central role in the susceptibility to, pathogenesis and treatment of mental disorders.

Schizophrenia (SCZ), bipolar disorder (BD) and recurrent major depressive disorder (rMDD) are common psychiatric illnesses. All have been associated with lower cognitive ability, and show evidence of genetic overlap and substantial evidence of pleiotropy with cognitive function and neuroticism. Disrupted in schizophrenia 1 (DISC1) protein directly interacts with a large set of proteins (DISC1 Interactome) that are involved in brain development and signaling. Modulation of DISC1 expression alters the expression of a circumscribed set of genes (DISC1 Regulome) that are also implicated in brain biology and disorder. Here, we report targeted sequencing of 59 DISC1 Interactome genes and 154 Regulome genes in 654 psychiatric patients and 889 cognitively-phenotyped control subjects, on whom we previously reported evidence for trait association from complete sequencing of the DISC1 locus. Burden analyses of rare and singleton variants predicted to be damaging were performed for psychiatric disorders, cognitive variables and personality traits. The DISC1 Interactome and Regulome showed differential association across the phenotypes tested. After family-wise error correction across all traits (FWERacross), an increased burden of singleton disruptive variants in the Regulome was associated with SCZ (FWERacrossP=0.0339). The burden of singleton disruptive variants in the DISC1 Interactome was associated with low cognitive ability at age 11 (FWERacrossP=0.0043). These results suggest that variants in the DISC1 Interactome effect the risk of psychiatric illness through altered expression of schizophrenia-associated genes. The biological impact of rare variants highlighted here merit further study.

Background Psychiatric illnesses are a group of genetically-related disorders with highly polygenic architecture and a significant environmental component. Even within families, these conditions show the attributes of many complex traits: reduced penetrance and phenotypic heterogeneity. An extended pedigree design has several advantages: it avoids population stratification and reduces genetic heterogeneity, narrowing the search for rare and functional variants that segregate with a phenotype. We have analysed a multigenerational pedigree where major mental illness segregates with a balanced translocation between chromosomes 1 and 11. Methods Whole genome sequencing was performed on 49 family members (20 carriers, 29 non-carriers of the translocation). Polygenic risk scores were calculated using summary statistics from the PGC MDD 2011 and used to predict diagnosis. Multipoint linkage analyses were performed using the variance components method implemented in SOLAR. Multiple phenotypic classes were used constructed to reflect the multiple phenotypes within the family. Fine-mapping was performed using two-point linkage analyses across the linked regions and association analyses performed in a Scottish cohort with measures of mental health, cognitive and personality traits (N= 6,555; 2,060 cases and 4,495 controls). Results Two genome-wide significant peaks with LOD > 5.5 were detected on the translocated chromosomes 1 and 11 with maximum linkage to schizophrenia, bipolar disorder, recurrent major depression and cyclothymia; as previously noted for the translocation itself. In addition, two further peaks, a second on chromosome 1 and a peak on chromosome 5, showed genome-wide significant linkage to affective disorder (bipolar disorder, and major depressive disorder). Polygenic risk scores of schizophrenia and bipolar disorder, but not major depressive disorder significantly predict mental illness in the family. Functional annotation of the whole genome sequence, and case-control association for affective disorder in the Scottish population, support a role for GRM5, CNTN5 and PDE4D in the phenotypic heterogeneity seen in the family. Discussion These results suggest that the high density of psychiatric illness in the t(1;11) family may be a combination of: direct effects of the translocation on the genes located at the breakpoint (DISC1, DISC2, DISC1FP), “locking together” of additional familial risk factors and the accumulation of common risk variants. We have identified additional modifying loci that may explain the variance in disease expression. Our findings suggest that pleiotropy may play a significant role and that this is now tractable by whole genome sequencing in families.

International audience; Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified. To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors.

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies., Wellcome Trust (London, England) (Core Award 090532/Z/09/Z), Wellcome Trust (London, England) (Senior Investigator Award 095552/Z/11/Z ), Wellcome Trust (London, England) (WT095908), Wellcome Trust (London, England) (WT109497), Wellcome Trust (London, England) (WT098051), Wellcome Trust (London, England) (WT086084/Z/08/Z), Wellcome Trust (London, England) (WT100956/Z/13/Z ), Wellcome Trust (London, England) (WT097307), Wellcome Trust (London, England) (WT0855322/Z/08/Z ), Wellcome Trust (London, England) (WT090770/Z/09/Z ), Wellcome Trust (London, England) (Major Overseas program in Vietnam grant 089276/Z.09/Z), Medical Research Council (Great Britain) (grant G0801823), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I02593X/1), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I021213/1), Zhongguo ke xue ji shu qing bao yan jiu suo. Office of 863 Programme of China (2012AA02A201), National Basic Research Program of China (2011CB809201), National Basic Research Program of China (2011CB809202), National Basic Research Program of China (2011CB809203), National Natural Science Foundation of China (31161130357), Shenzhen Municipal Government of China (grant ZYC201105170397A), Canadian Institutes of Health Research (grant 136855), Quebec Ministry of Economic Development, Innovation, and Exports (PSR-SIIRI-195), Germany. Bundesministerium für Bildung und Forschung (0315428A), Germany. Bundesministerium für Bildung und Forschung (01GS08201), Germany. Bundesministerium für Bildung und Forschung (BMBF-EPITREAT grant 0316190A), Deutsche Forschungsgemeinschaft (Emmy Noether Grant KO4037/1-1), Beatriu de Pinos Program (2006 BP-A 10144), Beatriu de Pinos Program (2009 BP-B 00274), Spanish National Institute for Health (grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER), Japan Society for the Promotion of Science (fellowship number PE13075), Marie Curie Actions Career Integration (grant 303772), Fonds National Suisse del la Recherche, SNSF, Scientifique (31003A_130342), National Center for Biotechnology Information (U.S.) (U54HG3067), National Center for Biotechnology Information (U.S.) (U54HG3273), National Center for Biotechnology Information (U.S.) (U01HG5211), National Center for Biotechnology Information (U.S.) (U54HG3079), National Center for Biotechnology Information (U.S.) (R01HG2898), National Center for Biotechnology Information (U.S.) (R01HG2385), National Center for Biotechnology Information (U.S.) (RC2HG5552), National Center for Biotechnology Information (U.S.) (U01HG6513), National Center for Biotechnology Information (U.S.) (U01HG5214), National Center for Biotechnology Information (U.S.) (U01HG5715), National Center for Biotechnology Information (U.S.) (U01HG5718), National Center for Biotechnology Information (U.S.) (U01HG5728), National Center for Biotechnology Information (U.S.) (U41HG7635), National Center for Biotechnology Information (U.S.) (U41HG7497), National Center for Biotechnology Information (U.S.) (R01HG4960), National Center for Biotechnology Information (U.S.) (R01HG5701), National Center for Biotechnology Information (U.S.) (R01HG5214), National Center for Biotechnology Information (U.S.) (R01HG6855), National Center for Biotechnology Information (U.S.) (R01HG7068), National Center for Biotechnology Information (U.S.) (R01HG7644), National Center for Biotechnology Information (U.S.) (DP2OD6514), National Center for Biotechnology Information (U.S.) (DP5OD9154), National Center for Biotechnology Information (U.S.) (R01CA166661), National Center for Biotechnology Information (U.S.) (R01CA172652), National Center for Biotechnology Information (U.S.) (P01GM99568), National Center for Biotechnology Information (U.S.) (R01GM59290), National Center for Biotechnology Information (U.S.) (R01GM104390), National Center for Biotechnology Information (U.S.) (T32GM7790), National Center for Biotechnology Information (U.S.) (R01HL87699), National Center for Biotechnology Information (U.S.) (R01HL104608), National Center for Biotechnology Information (U.S.) (T32HL94284), National Center for Biotechnology Information (U.S.) (HHSN268201100040C), National Center for Biotechnology Information (U.S.) (HHSN272201000025C), Lundbeck Foundation (grant R170-2014-1039, Simons Foundation (SFARI award SF51), National Science Foundation (U.S.) (Research Fellowship DGE-1147470)

Summary: AnnTools is a versatile bioinformatics application designed for comprehensive annotation of a full spectrum of human genome variation: novel and known single-nucleotide substitutions (SNP/SNV), short insertions/deletions (INDEL) and structural variants/copy number variation (SV/CNV). The variants are interpreted by interrogating data compiled from 15 constantly updated sources. In addition to detailed functional characterization of the coding variants, AnnTools searches for overlaps with regulatory elements, disease/trait associated loci, known segmental duplications and artifact prone regions, thereby offering an integrated and comprehensive analysis of genomic data. The tool conveniently accepts user-provided tracks for custom annotation and offers flexibility in input data formats. The output is generated in the universal Variant Call Format. High annotation speed makes AnnTools suitable for high-throughput sequencing facilities, while a low-memory footprint and modest CPU requirements allow it to operate on a personal computer. The application is freely available for public use; the package includes installation scripts and a set of helper tools. Availability: http://anntools.sourceforge.net/ Contact: vladimir.makarov@mssm.edu; chris.yoon@mssm.edu Supplementary information: Supplementary data are available at Bioinformatics online.