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One of the most significant risk variants for Parkinson’s disease (PD), rs356182, is located at the PD-associated locus near the alpha-synuclein (α-syn) encoding gene, SNCA. SNCA-proximal variants, including rs356182, are thought to function in PD risk through enhancers via allele-specific regulatory effects on SNCA expression. However, this interpretation discounts the complex activity of genetic enhancers and possible non-conical functions of α-syn. Here we investigated a novel risk mechanism for rs356182. We use CRISPR-Cas9 in LUHMES cells, a model for dopaminergic midbrain neurons, to generate precise hemizygous lesions at rs356182. The PD-protective (A/−), PD-risk (G/−) and wild-type (A/G) clones were neuronally differentiated and then compared transcriptionally and morphologically. Among the affected genes was SNCA, whose expression was promoted by the PD-protective allele (A) and repressed in its absence. In addition to SNCA, hundreds of genes were differentially expressed and associated with neurogenesis and axonogenesis—an effect not typically ascribed to α-syn. We also found that the transcription factor FOXO3 specifically binds to the rs356182 A-allele in differentiated LUHMES cells. Finally, we compared the results from the rs356182-edited cells to our previously published knockouts of SNCA and found only minimal overlap between the sets of significant differentially expressed genes. Together, the data implicate a risk mechanism for rs356182 in which the risk-allele (G) is associated with abnormal neuron development, independent of SNCA expression. We speculate that these pathological effects manifest as a diminished population of dopaminergic neurons during development leading to the predisposition for PD later in life.

Supplementary Table S1. Associations of Overall Breast Cancer Risk with 74 Breast Cancer Risk Variants in African Americans with Study-specific Results.

Supplementary Figure S1, Supplementary Figure S1. Regional plots of 3p24, 11q13, 12p11, 14q13, 16q12/TOX3, 16q12/FTO, 16q23, and 19p13.

This file contains: Supplementary Figure 1 (Related to Figure 2): Haplotype frequency for tiles Enhancer Scanning times with multiple SNPs. Supplementary Figure 2 (Related to Figure 3): Conservation and S/MAR predicted sequences at the locus. Supplementary Figure 3: Study overview and Overlap between the set of 134 SNPs obtained through the LD-guided analysis and the set of 40 SNPs obtained through the fine mapping-guided approach. Supplementary Figure 4 (Related to Figure 5): BNC2 binds to its own promoter. Extended data and detailed methods (including QC metrics) for BNC2 ChIP-Seq.

Genes selected for NanoString analysis. Contains the following tabs: (1) Nanostring gene set: final list for NanoString analysis. Gene Symbol, genes selected for nanostring analysis; Pathway, annotation from literature or from pathways in Tab 10; Cell line, cell line (FTE, iFTSEC283; OSE, iOSE11) in which the BNC2 ChIP-Seq peak was identified in proximity to the TSS. P-value, significance of expression changes using a nominal p-value {less than or equal to} 0.05 (indicated in green highlight); (2) 995 gene list: list of 995 genes/transcripts with TSS within 30 kb of the BNC2 ChIP-Seq peak centers found in both iOSE11 and iFTSEC283 cells; (3)-(9) Coordinates and annotation of BNC2 ChIP-seq peaks and genes with TSS within 30 kb of the BNC2 ChIP-seq peak centers from two replicates each of FTE (iFTSEC283) and OSE (iOSE11) cells, their overlaps; (10) Panther GO analysis results.

Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer.Significance:Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene.See related commentary by Choi and Brown, p. 439

Supplementary Fig Leg

Primers used in this study.

Fine mapping association results. Contains univariate and conditional (conditioning on rs3814113) analysis.

List of 134 SNPs in linkage disequilibrium (r2 {greater than or equal to} 0.3) with rs3814113 (based on 1000GP v3), selected for functional analysis.

eQTL Associations from GTEx (Release V7 (dbGaP Accession phs000424.v7.p2). Contains single gene eQTLs for BNC2, CNTLN, c9orf92 and SH3GL2 in all tissues and single SNP eQTL for all 40 SNPs in the credible candidate set.

Supplementary Methods and Tables

Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits.Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background.Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis.Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures.Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.

Background: Genome-wide association studies have identified approximately 100 common genetic variants associated with breast cancer risk, the majority of which were discovered in women of European ancestry. Because of different patterns of linkage disequilibrium, many of these genetic markers may not represent signals in populations of African ancestry.Methods: We tested 74 breast cancer risk variants and conducted fine-mapping of these susceptibility regions in 6,522 breast cancer cases and 7,643 controls of African ancestry from three genetic consortia (AABC, AMBER, and ROOT).Results: Fifty-four of the 74 variants (73%) were found to have ORs that were directionally consistent with those previously reported, of which 12 were nominally statistically significant (P < 0.05). Through fine-mapping, in six regions (3p24, 12p11, 14q13, 16q12/FTO, 16q23, 19p13), we observed seven markers that better represent the underlying risk variant for overall breast cancer or breast cancer subtypes, whereas in another two regions (11q13, 16q12/TOX3), we identified suggestive evidence of signals that are independent of the reported index variant. Overlapping chromatin features and regulatory elements suggest that many of the risk alleles lie in regions with biological functionality.Conclusions: Through fine-mapping of known susceptibility regions, we have revealed alleles that better characterize breast cancer risk in women of African ancestry.Impact: The risk alleles identified represent genetic markers for modeling and stratifying breast cancer risk in women of African ancestry. Cancer Epidemiol Biomarkers Prev; 26(7); 1016–26. ©2017 AACR.

Supplementary Data 1-4 from Control of Androgen Receptor Signaling in Prostate Cancer by the Cochaperone Small Glutamine–Rich Tetratricopeptide Repeat Containing Protein α

There is emerging evidence that the balance between estrogen receptor-α (ERα) and androgen receptor (AR) signaling is a critical determinant of growth in the normal and malignant breast. In this study, we assessed AR status in a cohort of 215 invasive ductal breast carcinomas. AR and ERα were coexpressed in the majority (80-90%) of breast tumor cells. Kaplan-Meier product limit analysis and multivariate Cox regression showed that AR is an independent prognostic factor in ERα-positive disease, with a low level of AR (less than median of 75% positive cells) conferring a 4.6-fold increased risk of cancer-related death (P = 0.002). Consistent with a role for AR in breast cancer outcome, AR potently inhibited ERα transactivation activity and 17β-estradiol–stimulated growth of breast cancer cells. Transfection of MDA-MB-231 breast cancer cells with either functionally impaired AR variants or the DNA-binding domain of the AR indicated that the latter is both necessary and sufficient for inhibition of ERα signaling. Consistent with molecular modeling, electrophoretic mobility shift assays showed binding of the AR to an estrogen-responsive element (ERE). Evidence for a functional interaction of the AR with an ERE in vivo was provided by chromatin immunoprecipitation data, revealing recruitment of the AR to the progesterone receptor promoter in T-47D breast cancer cells. We conclude that, by binding to a subset of EREs, the AR can prevent activation of target genes that mediate the stimulatory effects of 17β-estradiol on breast cancer cells. [Cancer Res 2009;69(15):6131–40]

Supplementary Tables 1-3 from Androgen Receptor Inhibits Estrogen Receptor-α Activity and Is Prognostic in Breast Cancer

Although the androgen receptor (AR) is accepted as the major determinant of prostate cancer cell survival throughout disease progression, it is currently unclear how the receptor sustains genomic signaling under conditions of systemic androgen ablation. Here, we show that the evolutionarily conserved Hsp70/Hsp90 cochaperone, small glutamine–rich tetratricopeptide repeat containing protein α (αSGT), interacts with the hinge region of the human AR in yeast and mammalian cells. Overexpression and RNA interference revealed that αSGT acts to (a) promote cytoplasmic compartmentalization of the AR, thereby silencing the receptors basal/ligand-independent transcriptional activity, (b) regulate the sensitivity of receptor signaling by androgens, and (c) limit the capacity of noncanonical ligands to induce AR agonist activity. Immunofluorescence, coactivator, and chromatin immunoprecipitation analyses strongly suggest that these effects of αSGT on AR function are mediated by interaction in the cytoplasm and are distinct from the receptors response to classic coregulators. Quantitative immunohistochemical analysis of αSGT and AR levels in a cohort of 32 primary and 64 metastatic human prostate cancers revealed dysregulation in the level of both proteins during disease progression. The significantly higher AR/αSGT ratio in metastatic samples is consistent with the sensitization of prostate tumor cells to androgen signaling with disease progression, particularly in a low-hormone environment. These findings implicate αSGT as a molecular rheostat of in vivo signaling competence by the AR, and provide new insight into the determinants of androgen sensitivity during prostate cancer progression. [Cancer Res 2007;67(20):10087–96]

Genetic risk for complex diseases very rarely reflects only Mendelian-inherited phenotypes where single-gene mutations can be followed in families by linkage analysis. More commonly, a large set of low-penetrance, small effect-size variants combine to confer risk; they are normally revealed in genome-wide association studies (GWAS), which compare large population groups. Whereas Mendelian inheritance points toward disease mechanisms arising from the mutated genes, in the case of GWAS signals, the effector proteins and even general risk mechanism are mostly unknown. Instead, the utility of GWAS currently lies primarily in predictive and diagnostic information. Although an amazing body of GWAS-based knowledge now exists, we advocate for more funding towards the exploration of the fundamental biology in post-GWAS studies; this research will bring us closer to causality and risk gene identification. Using Parkinson’s Disease as an example, we ask, how, where, and when do risk loci contribute to disease?

Parkinson's disease (PD) pathogenesis may involve the epigenetic control of enhancers that modify neuronal functions. Here, we comprehensively examine DNA methylation at enhancers, genome-wide, in neurons of patients with PD and of control individuals. We find a widespread increase in cytosine modifications at enhancers in PD neurons, which is partly explained by elevated hydroxymethylation levels. In particular, patients with PD exhibit an epigenetic and transcriptional upregulation of TET2, a master-regulator of cytosine modification status. TET2 depletion in a neuronal cell model results in cytosine modification changes that are reciprocal to those observed in PD neurons. Moreover, Tet2 inactivation in mice fully prevents nigral dopaminergic neuronal loss induced by previous inflammation. Tet2 loss also attenuates transcriptional immune responses to an inflammatory trigger. Thus, widespread epigenetic dysregulation of enhancers in PD neurons may, in part, be mediated by increased TET2 expression. Decreased Tet2 activity is neuroprotective, in vivo, and may be a new therapeutic target for PD.

As researchers grapple with the mechanisms and implications of alpha-synuclein (α-syn) in neuropathology, it is often forgotten that the function(s) of α-syn in healthy cells remain largely elusive. Previous work has relied on observing α-syn localization in the cell or using knockout mouse models. Here, we address the specific role of α-syn in human dopaminergic neurons by disrupting its gene (SNCA) in the human dopaminergic neuron cell line, LUHMES. SNCA-null cells were able to differentiate grossly normally and showed modest effects on gene expression. The effects on gene expression were monodirectional, resulting primarily in the significant decrease of expression for 401 genes, implicating them as direct, or indirect positive targets of α-syn. Gene ontological analysis of these genes showed enrichment in terms associated with proliferation, differentiation, and synapse activity. These results add to the tapestry of α-syn biological functions. SIGNIFICANCE STATEMENT: The normal functions of α-syn have remained controversial, despite its clear importance in Parkinson's Disease pathology, where it accumulates in Lewy bodies and contributes to neurodegeneration. Its name implies synaptic and nuclear functions, but how it participates at these locations has not been resolved. Via knock-out experiments in dopaminergic neurons, we implicate α-syn as a functional participant in synapse activity and in proliferation/differentiation, the latter being novel and provide insight into α-syn's role in neuronal development.

Alpha-synuclein accumulation in dopaminergic neurons is one of the primary features of Parkinson’s disease (PD). Despite its toxic properties during PD, alpha-synuclein has some important physiological functions. Although the activity of the protein has been extensively studied in neurons, the protein is also expressed in other cell types including immune cells and glia. Genetic studies show that mutations in synuclein alpha (SNCA), the gene that encodes alpha-synuclein, and alterations in its expression levels are a significant risk factor for PD, which likely impact the functions of a broad range of cell types. The consequences of altered SNCA expression in other cell types is beginning to be explored. Microglia, the primary macrophage population in the Central Nervous System (CNS), for example, are affected by variations in alpha-synuclein levels and functions. Studies suggest that deviations of alpha-synuclein’s normal activity influence hematopoiesis, the process that gives rise to microglia, and microglia’s immune functions. Alpha-synuclein levels also dictate the efficiency of SNARE-mediated vesicle formation, which could influence autophagy and cytokine release in microglia. Starting from the time of conception, these effects could impact one’s risk for developing PD. Further studies are needed to determine the physiological role of alpha-synuclein and how the protein is affected during PD in non-neuronal cells such as microglia. In this review we will discuss the known roles of alpha-synuclein in differentiation, immune responses, and vesicle formation, with insights into how abnormal alpha-synuclein expression and activity are linked to altered functions of microglia during PD.

SUMMARYOne of the most significant Parkinson’s disease (PD) risk variants, rs356182, is located at the PD-associated locus near the alpha-synuclein encoding gene, SNCA. SNCA-proximal variants, including rs356182, are thought to function in PD via allele-specific regulatory effects on SNCA expression. However, this interpretation discounts the complex activity of genetic enhancers and possible nonconical effects of alpha-synuclein. Here we investigate a novel risk mechanism for rs356182. We use CRISPR-Cas9 in LUHMES cells, a model for dopaminergic neurons, to generate precise hemizygous lesions at rs356182. The PD-protective (A/-), PD-risk (G/-), and WT (A/G) strains are differentiated into dopaminergic neurons then compared transcriptionally and morphologically. We observe effects not typically ascribed to SNCA; hundreds of differentially expressed genes associated with neuronal differentiation and axonogenesis. Together, the data implicate a risk mechanism for rs356182 in which the risk-allele (G) is associated with abnormal neuronal differentiation. We speculate the disease-relevant effect originates as a diminished population of DA neurons leading to the predisposition for PD later in life.

This opinion paper highlights strategies for a better understanding of non-Mendelian genetic risk that was revealed by genome-wide association studies (GWAS) of complex diseases. The genetic risk resides predominantly in non-coding regulatory DNA, such as in enhancers. The identification of mechanisms, the causal variants (mainly SNPs), and their target genes are, however, not always apparent but are likely involved in a network of risk determinants; the identification presents a bottle-neck in the full understanding of the genetics of complex phenotypes. Here, we propose strategies to identify functional SNPs and link risk enhancers with their target genes. The strategies are 1) identifying finemapped SNPs that break/form response elements within chromatin bio-features in relevant cell types 2) considering the nearest gene on linear DNA, 3) analyzing eQTLs, 4) mapping differential DNA methylation regions and relating them to gene expression, 5) employing genomic editing with CRISPR/cas9 and 6) identifying topological associated chromatin domains using chromatin conformation capture.

Background Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10−8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. Methods We conducted a GWAS in European descent CRC cases and control subjects using a discovery–replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10−8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. Results The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10−8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. Conclusions This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.

The lateralization of the human brain may provide clues into the pathogenesis and progression of neurodegenerative diseases. Though differing in their presentation and underlying pathologies, neurodegenerative diseases are all devastating and share an intriguing theme of asymmetrical pathology and clinical symptoms. Parkinson’s disease, with its distinctive onset of motor symptoms on one side of the body, stands out in this regard, but a review of the literature reveals asymmetries in several other neurodegenerative diseases. Here, we review the lateralization of the structure and function of the healthy human brain and the common genetic and epigenetic patterns contributing to the development of asymmetry in health and disease. We specifically examine the role of asymmetry in Parkinson’s disease, Alzheimer’s disease, amyotrophic lateral sclerosis, and multiple sclerosis, and interrogate whether these imbalances may reveal meaningful clues about the origins of these diseases. We also propose several hypotheses for how lateralization may contribute to the distinctive and enigmatic features of asymmetry in neurodegenerative diseases, suggesting a role for asymmetry in the choroid plexus, neurochemistry, protein distribution, brain connectivity and the vagus nerve. Finally, we suggest how future studies may reveal novel insights into these diseases through the lens of asymmetry., Lubben et al. review the lateralization of the CNS in the context of the common asymmetric phenotypes among neurodegenerative diseases. This evidence suggests that lateralization may confer vulnerability to one brain hemisphere, providing clues to the pathogeneses and progression of these neurological diseases, which merit further research., Graphical Abstract Graphical Abstract

Genome-wide association studies (GWAS) have uncovered thousands of single nucleotide polymorphisms (SNPs) that are associated with Parkinson’s disease (PD) risk. The functions of most of these SNPs, including the cell type they influence, and how they affect PD etiology remain largely unknown. To identify functional SNPs, we aligned PD risk SNPs within active regulatory regions of DNA in microglia, a cell type implicated in PD development. Out of 6,749 ‘SNPs of interest’ from the most recent PD GWAS metanalysis, 73 were located in open regulatory chromatin as determined by both ATAC-seq and H3K27ac ChIP-seq. We highlight a subset of SNPs that are favorable candidates for further mechanistic studies. These SNPs are located in regulatory DNA at the SLC50A1, SNCA, BAG3, FBXL19, SETD1A, and NUCKS1 loci. A network analysis of the genes with risk SNPs in their promoters, implicated substance transport, involving autophagy and lysosomal genes. Our study provides a more focused set of risk SNPs and their associated risk genes as candidates for further follow-up studies, which will help identify mechanisms in microglia that increase the risk for PD.

Background Recent genome-wide association studies (GWAS) have identified more than 100 loci associated with increased risk of prostate cancer, most of which are in non-coding regions of the genome. Understanding the function of these non-coding risk loci is critical to elucidate the genetic susceptibility to prostate cancer. Results We generate genome-wide regulatory element maps and performed genome-wide chromosome confirmation capture assays (in situ Hi-C) in normal and tumorigenic prostate cells. Using this information, we annotate the regulatory potential of 2,181 fine-mapped prostate cancer risk-associated SNPs and predict a set of target genes that are regulated by prostate cancer risk-related H3K27Ac-mediated loops. We next identify prostate cancer risk-associated CTCF sites involved in long-range chromatin loops. We use CRISPR-mediated deletion to remove prostate cancer risk-associated CTCF anchor regions and the CTCF anchor regions looped to the prostate cancer risk-associated CTCF sites, and we observe up to 100-fold increases in expression of genes within the loops when the prostate cancer risk-associated CTCF anchor regions are deleted. Conclusions We identify GWAS risk loci involved in long-range loops that function to repress gene expression within chromatin loops. Our studies provide new insights into the genetic susceptibility to prostate cancer. Electronic supplementary material The online version of this article (10.1186/s13059-018-1531-0) contains supplementary material, which is available to authorized users.

Genome-wide association studies of Parkinson's disease have revealed polymorphic variants associated with closely mapped genes of interest. We propose here that those genes may only represent the tip of an iceberg of regulatory effects and do not necessary reflect disease relevance. To usefully interpret a risk locus, one needs to consider 5 dimensions of information, which represent the three-dimensional structure of chromatin (dimensions #1- 3), which is locally variable across time (dimension #4), and, most importantly, dependent on cell type and context (dimension #5).

Parkinson's disease (PD) pathogenesis may involve the epigenetic control of enhancers that modify neuronal functions. Here, we comprehensively examine DNA methylation at enhancers, genome-wide, in neurons of patients with PD and of control individuals. We find a widespread increase in cytosine modifications at enhancers in PD neurons, which is partly explained by elevated hydroxymethylation levels. In particular, patients with PD exhibit an epigenetic and transcriptional upregulation of TET2, a master-regulator of cytosine modification status. TET2 depletion in a neuronal cell model results in cytosine modification changes that are reciprocal to those observed in PD neurons. Moreover, Tet2 inactivation in mice fully prevents nigral dopaminergic neuronal loss induced by previous inflammation. Tet2 loss also attenuates transcriptional immune responses to an inflammatory trigger. Thus, widespread epigenetic dysregulation of enhancers in PD neurons may, in part, be mediated by increased TET2 expression. Decreased Tet2 activity is neuroprotective, in vivo, and may be a new therapeutic target for PD.

Background: Breast cancer genetic predisposition is governed by more than 142 loci as revealed by genome-wide association studies (GWAS). The functional contribution of these risk loci to breast cancer remains unclear, and additional post-GWAS analyses are required. Methods: We identified active regulatory elements (enhancers, promoters, and chromatin organizing elements) by histone H3K27 acetylation and CTCF occupancy and determined the enrichment of risk variants at these sites. We compared these results with previously published data and for other cell lines, including human mammary epithelial cells, and related these data to gene expression. Results: In terms of mapping accuracy and resolution, our data augment previous annotations of the MCF-7 epigenome. After intersection with GWAS risk variants, we found 39 enhancers and 15 CTCF occupancy sites that, between them, overlapped 96 breast cancer credible risk variants at 42 loci. These risk enhancers likely regulate the expression of dozens of genes, which are enriched for GO categories, including estrogen and prolactin signaling. Conclusions: Ten (of 142) breast cancer risk loci likely function via enhancers that are active in MCF-7 and are well suited to targeted manipulation in this system. In contrast, risk loci cannot be mapped to specific CTCF-binding sites, and the genes linked to risk CTCF sites did not show functional enrichment. The identity of risk enhancers and their associated genes suggests that some risk may function during later processes in cancer progression. Impact: Here, we report how the ER+ cell line MCF-7 can be used to dissect risk mechanisms for breast cancer.

An emerging treatment for Parkinson's disease (PD) is cell replacement therapy. Authentic midbrain dopaminergic (mDA) neuronal precursors can be differentiated from human embryonic stem cells (hESCs) and human induced pluripotent stem cells (iPSCs). These laboratory‐generated mDA cells have been demonstrated to mature into functional dopaminergic neurons upon transplantation into preclinical models of PD. However, clinical trials with human fetal mesenchephalic cells have shown that cell replacement grafts in PD are susceptible to Lewy body formation suggesting host‐to‐graft transfer of α‐synuclein pathology. Here, we have used CRISPR/Cas9n technology to delete the endogenous SNCA gene, encoding for α‐synuclein, in a clinical‐grade hESC line to generate SNCA +/− and SNCA −/− cell lines. These hESC lines were first differentiated into mDA neurons, and then challenged with recombinant α‐synuclein preformed fibrils (PFFs) to seed the formation for Lewy‐like pathology as measured by phosphorylation of serine‐129 of α‐synuclein (pS129‐αSyn). Wild‐type neurons were fully susceptible to the formation of protein aggregates positive for pS129‐αSyn, while SNCA +/− and SNCA −/− neurons exhibited significant resistance to the formation of this pathological mark. This work demonstrates that reducing or completely removing SNCA alleles by CRISPR/Cas9n‐mediated gene editing confers a measure of resistance to Lewy pathology.

Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. Significance: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene. See related commentary by Choi and Brown, p. 439

In genome-wide association studies of complex diseases, many risk polymorphisms are found to lie in non-coding DNA and likely confer risk through allele-dependent differences in gene regulatory elements. However, because distal regulatory elements can alter gene expression at various distances on linear DNA, the identity of relevant genes is unknown for most risk loci. In Parkinson's disease, at least some genetic risk is likely intrinsic to a neuronal subpopulation of cells in the brain regions affected. In order to compare neuron-relevant methods of pairing risk polymorphisms to target genes as well as to further characterize a single-cell model of a neurodegenerative disease, we used the portionally-dopaminergic, neuronal, mesencephalic-derived cell line LUHMES to dissect differentiation-specific mechanisms of gene expression. We compared genome-wide gene expression in undifferentiated and differentiated cells with genome-wide histone H3K27ac and CTCF-bound regions. Whereas promoters and CTCF binding were largely consistent between differentiated and undifferentiated cells, enhancers were mostly unique. We matched the differentiation-specific appearance or disappearance of enhancers with changes in gene expression and identified 22,057 enhancers paired with 6388 differentially expressed genes by proximity. These enhancers are enriched with at least 13 transcription factor response elements, driving a cluster of genes involved in neurogenesis. We show that differentiated LUHMES cells, but not undifferentiated cells, show enrichment for PD-risk SNPs. Candidate genes for these loci are largely unrelated, though a subset is linked to synaptic vesicle cycling and transport, implying that PD-related disruption of these pathways is intrinsic to dopaminergic neurons.

Genome-wide association studies (GWAS) have linked dozens of single nucleotide polymorphisms (SNPs) with Parkinson's disease (PD) risk. Ascertaining the functional and eventual causal mechanisms underlying these relationships has proven difficult. The majority of risk SNPs, and nearby SNPs in linkage disequilibrium (LD), are found in intergenic or intronic regions and confer risk through allele-dependent expression of multiple unknown target genes. Combining GWAS results with publicly available GTEx data, generated through eQTL (expression quantitative trait loci) identification studies, enables a direct association of SNPs to gene expression levels and aids in narrowing the large population of potential genetic targets for hypothesis-driven experimental cell biology. Separately, overlapping of SNPs with putative enhancer segmentations can strengthen target filtering. We report here the results of analyzing 7,607 PD risk SNPs along with an additional 23,759 high linkage disequilibrium-associated variants paired with eQTL gene expression. We found that enrichment analysis on the set of genes following target filtering pointed to a single large LD block at 6p21 that contained multiple HLA-MHC-II genes. These MHC-II genes remain associated with PD when the genes were filtered for correlation between GWAS significance and eQTL levels, strongly indicating a direct effect on PD etiology.

Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.

Development of high-throughput sequencing-based methods has enabled us to examine nuclear architecture at unprecedented resolution, allowing further examination of the function of long-range chromosomal interactions. Here, we review methods used to investigate novel long-range chromosomal interactions and genome-wide organization of chromatin. We further discuss transcriptional activation and silencing in relation to organization and positioning of gene loci and regulation of chromatin organization through protein complexes and noncoding RNAs.

Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.

Background Although technological advances now allow increased tumor profiling, a detailed understanding of the mechanisms leading to the development of different cancers remains elusive. Our approach toward understanding the molecular events that lead to cancer is to characterize changes in transcriptional regulatory networks between normal and tumor tissue. Because enhancer activity is thought to be critical in regulating cell fate decisions, we have focused our studies on distal regulatory elements and transcription factors that bind to these elements. Results Using DNA methylation data, we identified more than 25,000 enhancers that are differentially activated in breast, prostate, and kidney tumor tissues, as compared to normal tissues. We then developed an analytical approach called Tracing Enhancer Networks using Epigenetic Traits that correlates DNA methylation levels at enhancers with gene expression to identify more than 800,000 genome-wide links from enhancers to genes and from genes to enhancers. We found more than 1200 transcription factors to be involved in these tumor-specific enhancer networks. We further characterized several transcription factors linked to a large number of enhancers in each tumor type, including GATA3 in non-basal breast tumors, HOXC6 and DLX1 in prostate tumors, and ZNF395 in kidney tumors. We showed that HOXC6 and DLX1 are associated with different clusters of prostate tumor-specific enhancers and confer distinct transcriptomic changes upon knockdown in C42B prostate cancer cells. We also discovered de novo motifs enriched in enhancers linked to ZNF395 in kidney tumors. Conclusions Our studies characterized tumor-specific enhancers and revealed key transcription factors involved in enhancer networks for specific tumor types and subgroups. Our findings, which include a large set of identified enhancers and transcription factors linked to those enhancers in breast, prostate, and kidney cancers, will facilitate understanding of enhancer networks and mechanisms leading to the development of these cancers. Electronic supplementary material The online version of this article (doi:10.1186/s13072-016-0102-4) contains supplementary material, which is available to authorized users.

Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers and cancer related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental and lifestyle related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. TRICL (Transdisciplinary Research for Cancer of Lung) and International Lung Cancer Consortium (ILCCO): National Institute of Health U19 CA148127-01 (C.I. Amos, J. Byun, Y. Li, X. Xiao, J. L. Forman, A. Risch, H. Bickeböller, M. Waldenberger, I. Brüske, J. Manz, P. Brennan, R. Hung, H. Shen, Y. Shi, A. Kamal, C. I. Amos, J.K. Field), Canadian Cancer Society Research Institute (no. 020214, R. Hung). DRIVE (Discovery, Biology, and Risk of Inherited Variants in Breast Cancer): National Institute of Health U19 CA148065 (D.J. Hazelett, D. F. Easton, S. Lindström, P. Kraft, J. Dennis, A. Dunning, K. Michailidou, L. Fachal, S. Benlloch, J. Cunningham, K. Butterbach, K. Offit, R. Schmutzler, L. Ottini, D. Vincent). CORECT (ColoRectal Transdisciplinary Study): National Institute of Health U19 CA148107; R01 CA81488, P30 CA014089 (S. Gruber, U. Peters, G. Casey). ELLIPSE (ELLIPSE, Elucidating Loci in Prostate Cancer Susceptibility): This work was support by U19 CA148537(F. Schumacher, S.A. Gayther, S.L. Schmit, C.K. Edlund, D.J. Hazelett, G.A. Coetzee, C. Haiman, S. Demetriades, D. Van Den Berg). FOCI (Transdisciplinary Cancer Genetic Association and Interacting Studies): National Institutes of Health U19 CA148112- 01 (T.A. Sellers, C. Phelan), R01-CA122443(B. Hicks) ) P50-CA116201, CA192393 (F. Couch), P50-CA136393(J. Cunningham, F. Couch), OCAC - CA-149429 (C. Phelan). , P30-CA15083 (B. Hicks), Cancer Research UK (C490/A8339(A. Antoniou, P. Pharoah, A. Dunning), C490/A16561(P. Pharoah, A. Dunning), C490/A10119 (A. Dunning, P. Pharoah), C490/A10124 (A. Dunning, P. Pharoah)). ASTERISK: a Hospital Clinical Research Program (PHRC) and supported by the Regional Council of Pays de la Loire, the Groupement des Entreprises Françaises dans la Lutte contre le Cancer (GEFLUC), the Association Anne de Bretagne Génétique and the Ligue Régionale Contre le Cancer (LRCC) (F. Bacot). DACHS: German Research Council (Deutsche Downloaded from cebp.aacrjournals.org on October 31, 2016. © 2016 American Association for Cancer Research. Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 3, 2016; DOI: 10.1158/1055-9965.EPI-16-0106 Forschungsgemeinschaft, BR 1704/6-1, BR 1704/6-3, BR 1704/6-4, and CH 117/1-1, C.K. Edlund), and the German Federal Ministry of Education and Research (01KH0404 and 01ER0814). Prostate Lung Colon Ovarian Screening trial: Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, NIH, DHHS. The GC-HBOC (German Consortium of Hereditary Breast and Ovarian Cancer) is supported by the German Cancer Aid (grant no 110837, coordinator: R. Schmutzler, Cologne). The PERSPECTIVE (J. Simard) project was supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research (MOP-86727, L.E. Kelemen), the Ministère de l’Économie, Innovation et Exportation du Québec through Genome Québec, and thee Quebec Breast Cancer Foundation, including additional funding from the Canadian Breast Cancer Foundation and the National Cancer Institute USA through Breast Cancer Family Registry Cohort (#1UM1CA164920-01A1). European Union Framework Programme for Research and Innovation (MSCA-IF-2014-EF-656144)(L. Fachal). The Breast Cancer Research Foundation, P30 CA08748, Andrew Sabin Foundation (K. Offit). CIDR genotyping for the Oncoarray was conducted under contract 268201200008I to K.Doheny and through grant 1X01HG007491- 01 to C.I. Amos. This is the author accepted manuscript. The final version is available from American Association for Cancer Research via http://dx.doi.org/10.1158/1055-9965.EPI-16-0106