SUMMARY The extent to which low-frequency (minor allele frequency [MAF] between 1–5%) and rare (MAF ≤ 1%) variants contribute to complex traits and disease in the general population is largely unknown. Bone mineral density (BMD) is highly heritable, is a major predictor of osteoporotic fractures and has been previously associated with common genetic variants1–8, and rare, population-specific, coding variants9. Here we identify novel non-coding genetic variants with large effects on BMD (ntotal = 53,236) and fracture (ntotal = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n=2,882 from UK10K), whole-exome sequencing (n= 3,549), deep imputation of genotyped samples using a combined UK10K/1000Genomes reference panel (n=26,534), and de-novo replication genotyping (n= 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size 4-fold larger than the mean of previously reported common variants for lumbar spine BMD8 (rs11692564[T], MAF = 1.7%, replication effect size = +0.20 standard deviations [SD], Pmeta = 2×10−14), which was also associated with a decreased risk of fracture (OR = 0.85; P = 2×10−11; ncases = 98,742 and ncontrols = 409,511). Using an En1Cre/flox mouse model, we observed that conditional loss of En1 results in low bone mass, likely as a consequence of high bone turn-over. We also identified a novel low-frequency non-coding variant with large effects on BMD near WNT16 (rs148771817[T], MAF = 1.1%, replication effect size = +0.39 SD, Pmeta = 1×10−11). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.

To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1 . In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P <5×10 −8 , bringing the number of known independent signals for CRC to approximately 100. New signals implicate lower-frequency variants, Krüppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs, somatic drivers, and support a role of immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of underlying biology, and impact personalized screening strategies and drug development.

To understand the genetic drivers of immune recognition and evasion in colorectal cancer, we analyzed 1,211 colorectal cancer primary tumor samples, including 179 classified as microsatellite instability-high (MSI-high). This set includes The Cancer Genome Atlas colorectal cancer cohort of 592 samples, completed and analyzed here. MSI-high, a hypermutated, immunogenic subtype of colorectal cancer, had a high rate of significantly mutated genes in important immune-modulating pathways and in the antigen presentation machinery, including biallelic losses of and genes due to copy-number alterations and copy-neutral loss of heterozygosity. WNT/β-catenin signaling genes were significantly mutated in all colorectal cancer subtypes, and activated WNT/β-catenin signaling was correlated with the absence of T-cell infiltration. This large-scale genomic analysis of colorectal cancer demonstrates that MSI-high cases frequently undergo an immunoediting process that provides them with genetic events allowing immune escape despite high mutational load and frequent lymphocytic infiltration and, furthermore, that colorectal cancer tumors have genetic and methylation events associated with activated WNT signaling and T-cell exclusion. This multi-omic analysis of 1,211 colorectal cancer primary tumors reveals that it should be possible to better monitor resistance in the 15% of cases that respond to immune blockade therapy and also to use WNT signaling inhibitors to reverse immune exclusion in the 85% of cases that currently do not. .

BACKGROUND & AIMS Heritable factors contribute to the development of colorectal cancer. Identifying the genetic loci associated with colorectal tumor formation could elucidate the mechanisms of pathogenesis. METHODS We conducted a genome-wide association study that included 14 studies, 12,696 cases of colorectal tumors (11,870 cancer, 826 adenoma), and 15,113 controls of European descent. The 10 most statistically significant, previously unreported findings were followed up in 6 studies; these included 3056 colorectal tumor cases (2098 cancer, 958 adenoma) and 6658 controls of European and Asian descent. RESULTS Based on the combined analysis, we identified a locus that reached the conventional genome-wide significance level at less than 5.0 × 10−8: an intergenic region on chromosome 2q32.3, close to nucleic acid binding protein 1 (most significant single nucleotide polymorphism: rs11903757; odds ratio [OR], 1.15 per risk allele; P = 3.7 × 10−8). We also found evidence for 3 additional loci with P values less than 5.0 × 10−7: a locus within the laminin gamma 1 gene on chromosome 1q25.3 (rs10911251; OR, 1.10 per risk allele; P = 9.5 × 10−8), a locus within the cyclin D2 gene on chromosome 12p13.32 (rs3217810 per risk allele; OR, 0.84; P = 5.9 × 10−8), and a locus in the T-box 3 gene on chromosome 12q24.21 (rs59336; OR, 0.91 per risk allele; P = 3.7 × 10−7). CONCLUSIONS In a large genome-wide association study, we associated polymorphisms close to nucleic acid binding protein 1 (which encodes a DNA-binding protein involved in DNA repair) with colorectal tumor risk. We also provided evidence for an association between colorectal tumor risk and polymorphisms in laminin gamma 1 (this is the second gene in the laminin family to be associated with colorectal cancers), cyclin D2 (which encodes for cyclin D2), and T-box 3 (which encodes a T-box transcription factor and is a target of Wnt signaling to β-catenin). The roles of these genes and their products in cancer pathogenesis warrant further investigation.

Although well studied in families at high-risk, the roles of mutations in the BRCA1 and BRCA2 genes are poorly understood in breast cancers in the general population, particularly in Black women and in age groups outside of the very young. We examined the prevalence and predictors of BRCA1 and BRCA2 mutations in 1,628 women with breast cancer and 674 women without breast cancer who participated in a multicenter population-based case-control study of Black and White women, 35 to 64 years of age. Among cases, 2.4% and 2.3% carried deleterious mutations in BRCA1 and BRCA2, respectively. BRCA1 mutations were significantly more common in White (2.9%) versus Black (1.4%) cases and in Jewish (10.2%) versus non-Jewish (2.0%) cases; BRCA2 mutations were slightly more frequent in Black (2.6%) versus White (2.1%) cases. Numerous familial and demographic factors were significantly associated with BRCA1 and, to a lesser extent, BRCA2 carrier status, when examined individually. In models considering all predictors together, early onset ages in cases and in relatives, family history of ovarian cancer, and Jewish ancestry remained strongly and significantly predictive of BRCA1 carrier status, whereas BRCA2 predictors were fewer and more modest in magnitude. Both the combinations of predictors and effect sizes varied across racial/ethnic and age groups. These results provide first-time prevalence estimates for BRCA1/BRCA2 in breast cancer cases among understudied racial and age groups and show key predictors of mutation carrier status for both White and Black women and women of a wide age spectrum with breast cancer in the general population.

We used data from 2 large international consortia to develop CRC risk calculation models that included genetic and environmental factors along with family history. These determine risk of CRC and starting ages for screening with greater accuracy than the family history only model, which is based on the current screening guideline. These scoring systems might serve as a first step toward developing individualized CRC prevention strategies.

In this study, we performed high-resolution array comparative genomic hybridization with an array of 4153 bacterial artificial chromosome clones to assess copy number changes in 44 archival breast cancers. The tumors were flow sorted to exclude non-tumor DNA and increase our ability to detect gene copy number changes. In these tumors, losses were more frequent than gains, and gains in 1q and loss in 16q were the most frequent alterations. We compared gene copy number changes in the tumors based on histologic subtype and estrogen receptor (ER) status, i.e., ER-negative infiltrating ductal carcinoma, ER-positive infiltrating ductal carcinoma, and ER-positive infiltrating lobular carcinoma. We observed a consistent association between loss in regions of 5q and ER-negative infiltrating ductal carcinoma, as well as more frequent loss in 4p16, 8p23, 8p21, 10q25, and 17p11.2 in ER-negative infiltrating ductal carcinoma compared with ER-positive infiltrating ductal carcinoma (adjusted P values < 0.05). We also observed high-level amplifications in ER-negative infiltrating ductal carcinoma in regions of 8q24 and 17q12 encompassing the c-myc and c-erbB-2 genes and apparent homozygous deletions in 3p21, 5q33, 8p23, 8p21, 9q34, 16q24, and 19q13. ER-positive infiltrating ductal carcinoma showed a higher frequency of gain in 16p13 and loss in 16q21 than ER-negative infiltrating ductal carcinoma. Correlation analysis highlighted regions of change commonly seen together in ER-negative infiltrating ductal carcinoma. ER-positive infiltrating lobular carcinoma differed from ER-positive infiltrating ductal carcinoma in the frequency of gain in 1q and loss in 11q and showed high-level amplifications in 1q32, 8p23, 11q13, and 11q14. These results indicate that array comparative genomic hybridization can identify significant differences in the genomic alterations between subtypes of breast cancer.

The mouse has become an indispensable and versatile model organism for the study of development, genetics, behavior, and disease. The application of comprehensive gene expression profiling technologies to compare normal and diseased tissues or to assess molecular alterations resulting from various experimental interventions has the potential to provide highly detailed qualitative and quantitative descriptions of these processes. Ideally, to interpret experimental data, the magnitude and diversity of gene expression for the system under study should be well characterized, yet little is known about the normal variation of mouse gene expression in vivo. To assess natural differences in murine gene expression, we used a 5406-clone spotted cDNA microarray to quantitate transcript levels in the kidney, liver, and testis from each of 6 normal male C57BL6 mice. We used ANOVA to compare the variance across the six mice to the variance among four replicate experiments performed for each mouse tissue. For the 6 kidney samples, 102 of 3,088 genes (3.3%) exhibited a statistically significant mouse variance at a level of 0.05. In the testis, 62 of 3,252 genes (1.9%) showed statistically significant variance, and in the liver, there were 21 of 2,514 (0.8%) genes with significantly variable expression. Immune-modulated, stress-induced, and hormonally regulated genes were highly represented among the transcripts that were most variable. The expression levels of several genes varied significantly in more than one tissue. These studies help to define the baseline level of variability in mouse gene expression and emphasize the importance of replicate microarray experiments.DNA microarray ͉ variation ͉ transcript ͉ ANOVA T he use of DNA microarrays to obtain qualitative and quantitative profiles of gene expression has increased dramatically over the past several years. Microarrays can provide rapid and accurate measurements of thousands of distinct transcripts simultaneously. Most of the microarray expression studies performed to date have used relatively controlled systems that are manipulable in vitro, such as single-cell organisms (e.g., yeast) and clonal cell lines (1-3). The technology has also been applied to more complex in vivo systems involving mammalian tissues and organs. Many of these studies have been performed by using the mouse as a model organism, in part because of the relative ease of genetic manipulation coupled with the extensive genomic, anatomical, and physiological synteny with humans.