PheWAS analysis on large-scale biobank data with PheTK.

Summary: With the rapid growth of genetic data linked to electronic health record data in huge cohorts, large-scale phenome-wide association study (PheWAS), have become powerful discovery tools in biomedical research. PheWAS is an analysis method to study phenotype associations utilizing longitudinal electronic health record (EHR) data. Previous PheWAS packages were developed mostly in the days of smaller biobanks and with earlier PheWAS approaches. PheTK was designed to simplify analysis and efficiently handle biobank-scale data. PheTK uses multithreading and supports a full PheWAS workflow including extraction of data from OMOP databases and Hail matrix tables as well as PheWAS analysis for both phecode version 1.2 and phecodeX. Benchmarking results showed PheTK took 64% less time than the R PheWAS package to complete the same workflow. PheTK can be run locally or on cloud platforms such as the All of Us Researcher Workbench ( All of Us ) or the UK Biobank (UKB) Research Analysis Platform (RAP). Availability and implementation: The PheTK package is freely available on the Python Package Index (PyPi) and on GitHub under GNU Public License (GPL-3) at https://github.com/nhgritctran/PheTK . It is implemented in Python and platform independent. The demonstration workspace for All of Us will be made available in the future as a featured workspace. Contact: PheTK@mail.nih.gov.

Comparison of phenomic profiles in the All of Us Research Program against the US general population and the UK Biobank.

IMPORTANCE: Knowledge gained from cohort studies has dramatically advanced both public and precision health. The All of Us Research Program seeks to enroll 1 million diverse participants who share multiple sources of data, providing unique opportunities for research. It is important to understand the phenomic profiles of its participants to conduct research in this cohort. OBJECTIVES: More than 280 000 participants have shared their electronic health records (EHRs) in the All of Us Research Program. We aim to understand the phenomic profiles of this cohort through comparisons with those in the US general population and a well-established nation-wide cohort, UK Biobank, and to test whether association results of selected commonly studied diseases in the All of Us cohort were comparable to those in UK Biobank. MATERIALS AND METHODS: We included participants with EHRs in All of Us and participants with health records from UK Biobank. The estimates of prevalence of diseases in the US general population were obtained from the Global Burden of Diseases (GBD) study. We conducted phenome-wide association studies (PheWAS) of 9 commonly studied diseases in both cohorts. RESULTS: This study included 287 012 participants from the All of Us EHR cohort and 502 477 participants from the UK Biobank. A total of 314 diseases curated by the GBD were evaluated in All of Us, 80.9% (N = 254) of which were more common in All of Us than in the US general population [prevalence ratio (PR) >1.1, P < 2 × 10-5]. Among 2515 diseases and phenotypes evaluated in both All of Us and UK Biobank, 85.6% (N = 2152) were more common in All of Us (PR >1.1, P < 2 × 10-5). The Pearson correlation coefficients of effect sizes from PheWAS between All of Us and UK Biobank were 0.61, 0.50, 0.60, 0.57, 0.40, 0.53, 0.46, 0.47, and 0.24 for ischemic heart diseases, lung cancer, chronic obstructive pulmonary disease, dementia, colorectal cancer, lower back pain, multiple sclerosis, lupus, and cystic fibrosis, respectively. DISCUSSION: Despite the differences in prevalence of diseases in All of Us compared to the US general population or the UK Biobank, our study supports that All of Us can facilitate rapid investigation of a broad range of diseases. CONCLUSION: Most diseases were more common in All of Us than in the general US population or the UK Biobank. Results of disease-disease association tests from All of Us are comparable to those estimated in another well-studied national cohort.

Systematic replication of smoking disease associations using survey responses and EHR data in the All of Us Research Program.

OBJECTIVE: The All of Us Research Program (All of Us) aims to recruit over a million participants to further precision medicine. Essential to the verification of biobanks is a replication of known associations to establish validity. Here, we evaluated how well All of Us data replicated known cigarette smoking associations. MATERIALS AND METHODS: We defined smoking exposure as follows: (1) an EHR Smoking exposure that used International Classification of Disease codes; (2) participant provided information (PPI) Ever Smoking; and, (3) PPI Current Smoking, both from the lifestyle survey. We performed a phenome-wide association study (PheWAS) for each smoking exposure measurement type. For each, we compared the effect sizes derived from the PheWAS to published meta-analyses that studied cigarette smoking from PubMed. We defined two levels of replication of meta-analyses: (1) nominally replicated: which required agreement of direction of effect size, and (2) fully replicated: which required overlap of confidence intervals. RESULTS: PheWASes with EHR Smoking, PPI Ever Smoking, and PPI Current Smoking revealed 736, 492, and 639 phenome-wide significant associations, respectively. We identified 165 meta-analyses representing 99 distinct phenotypes that could be matched to EHR phenotypes. At P < .05, 74 were nominally replicated and 55 were fully replicated. At P < 2.68 × 10-5 (Bonferroni threshold), 58 were nominally replicated and 40 were fully replicated. DISCUSSION: Most phenotypes found in published meta-analyses associated with smoking were nominally replicated in All of Us. Both survey and EHR definitions for smoking produced similar results. CONCLUSION: This study demonstrated the feasibility of studying common exposures using All of Us data.

A test of automated use of electronic health records to aid in diagnosis of genetic disease.

PURPOSE: Automated use of electronic health records may aid in decreasing the diagnostic delay for rare diseases. The phenotype risk score (PheRS) is a weighted aggregate of syndromically related phenotypes that measures the similarity between an individual's conditions and features of a disease. For some diseases, there are individuals without a diagnosis of that disease who have scores similar to diagnosed patients. These individuals may have that disease but not yet be diagnosed. METHODS: We calculated the PheRS for cystic fibrosis (CF) for 965,626 subjects in the Vanderbilt University Medical Center electronic health record. RESULTS: Of the 400 subjects with the highest PheRS for CF, 248 (62%) had been diagnosed with CF. Twenty-six of the remaining participants, those who were alive and had DNA available in the linked DNA biobank, underwent clinical review and sequencing analysis of CFTR and SERPINA1. This uncovered a potential diagnosis for 2 subjects, 1 with CF and 1 with alpha-1-antitrypsin deficiency. An additional 7 subjects had pathogenic or likely pathogenic variants, 2 in CFTR and 5 in SERPINA1. CONCLUSION: These findings may be clinically actionable for the providers caring for these patients. Importantly, this study highlights feasibility and challenges for future implications of this approach.

Ontologizing health systems data at scale: making translational discovery a reality.

Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68-99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.

Genetic and clinical determinants of telomere length.

Many epidemiologic studies have identified important relationships between leukocyte telomere length (LTL) with genetics and health. Most of these studies have been significantly limited in scope by focusing predominantly on individual diseases or restricted to GWAS analysis. Using two large patient populations derived from Vanderbilt University and Marshfield Clinic biobanks linked to genomic and phenomic data from medical records, we investigated the inter-relationship between LTL, genomics, and human health. Our GWAS confirmed 11 genetic loci previously associated with LTL and two novel loci in SCNN1D and PITPNM1. PheWAS of LTL identified 67 distinct clinical phenotypes associated with both short and long LTL. We demonstrated that several diseases associated with LTL were related to one another but were largely independent from LTL genetics. Age of death was correlated with LTL independent of age. Those with very short LTL (<-1.5 standard deviation [SD]) died 10.4 years (p < 0.0001) younger than those with average LTL (±0.5 SD; mean age of death = 74.2 years). Likewise, those with very long LTL (>1.5 SD) died 1.9 years (p = 0.0175) younger than those with average LTL. This is consistent with the PheWAS results showing diseases associating with both short and long LTL. Finally, we estimated that the genome (12.8%) and age (8.5%) explain the largest proportion of LTL variance, whereas the phenome (1.5%) and sex (0.9%) explained a smaller fraction. In total, 23.7% of LTL variance was explained. These observations provide the rationale for expanded research to understand the multifaceted correlations between TL biology and human health over time, leading to effective LTL usage in medical applications.

Mapping the reaction zones for CdTe magic-sized clusters and their emission properties.

CdTe magic-sized clusters (MSCs) are promising building blocks for semiconductor devices because of their single size, consistent properties, and reproducible synthesis. However, the synthetic conditions for CdTe MSCs vary significantly in different reports, which hinders the general understanding of their formation mechanisms. Here, we employed Cd(oleate)2, trioctylphosphine telluride (TOPTe), and oleylamine, which are commonly used for larger quantum dot (QD) synthesis, as standard reaction precursors, and systematically investigated the effects of solvent, phosphine amount, oleylamine amount, Cd : Te ratio, and temperature on the evolution of MSCs with time. These conditions compose the "reaction coordinates" to map out the "reaction zones" for CdTe MSCs and QDs. We found that CdTe MSCs with the first excitonic transition (E1) at 449 nm can be synthesized in high purity with excess TOPTe using toluene as the solvent at 100 °C. Whereas higher temperature, excess of Cd(oleate)2, or more viscous solvent led to the aggregation of 449 nm MSC into larger magic-sized species with E1 at 469 nm as well as QDs with E1 > 500 nm. Increasing phosphine concentration simply enhanced the rate and yield of CdTe MSCs, while a critical amount of oleylamine was required to "turn on" the MSC formation. Interestingly, the pure 449 nm MSCs were non-emissive, but colorful emissions were observed for the reaction mixtures containing both MSCs and QDs. The emissions could be attributed to a small amount of QDs formed during the reaction. The mapping of reaction zones is a crucial step towards the rational synthesis of CdTe MSCs and further understanding of their formation mechanism.

Association between germline variants and somatic mutations in colorectal cancer.

Colorectal cancer (CRC) is a heterogeneous disease with evidence of distinct tumor types that develop through different somatically altered pathways. To better understand the impact of the host genome on somatically mutated genes and pathways, we assessed associations of germline variations with somatic events via two complementary approaches. We first analyzed the association between individual germline genetic variants and the presence of non-silent somatic mutations in genes in 1375 CRC cases with genome-wide SNPs data and a tumor sequencing panel targeting 205 genes. In the second analysis, we tested if germline variants located within previously identified regions of somatic allelic imbalance were associated with overall CRC risk using summary statistics from a recent large scale GWAS (n≃125 k CRC cases and controls). The first analysis revealed that a variant (rs78963230) located within a CNA region associated with TLR3 was also associated with a non-silent mutation within gene FBXW7. In the secondary analysis, the variant rs2302274 located in CDX1/PDGFRB frequently gained/lost in colorectal tumors was associated with overall CRC risk (OR = 0.96, p = 7.50e-7). In summary, we demonstrate that an integrative analysis of somatic and germline variation can lead to new insights about CRC.

Association of Pathogenic Variants in Hereditary Cancer Genes With Multiple Diseases.

Importance: Knowledge about the spectrum of diseases associated with hereditary cancer syndromes may improve disease diagnosis and management for patients and help to identify high-risk individuals. Objective: To identify phenotypes associated with hereditary cancer genes through a phenome-wide association study. Design, Setting, and Participants: This phenome-wide association study used health data from participants in 3 cohorts. The Electronic Medical Records and Genomics Sequencing (eMERGEseq) data set recruited predominantly healthy individuals from 10 US medical centers from July 16, 2016, through February 18, 2018, with a mean follow-up through electronic health records (EHRs) of 12.7 (7.4) years. The UK Biobank (UKB) cohort recruited participants from March 15, 2006, through August 1, 2010, with a mean (SD) follow-up of 12.4 (1.0) years. The Hereditary Cancer Registry (HCR) recruited patients undergoing clinical genetic testing at Vanderbilt University Medical Center from May 1, 2012, through December 31, 2019, with a mean (SD) follow-up through EHRs of 8.8 (6.5) years. Exposures: Germline variants in 23 hereditary cancer genes. Pathogenic and likely pathogenic variants for each gene were aggregated for association analyses. Main Outcomes and Measures: Phenotypes in the eMERGEseq and HCR cohorts were derived from the linked EHRs. Phenotypes in UKB were from multiple sources of health-related data. Results: A total of 214 020 participants were identified, including 23 544 in eMERGEseq cohort (mean [SD] age, 47.8 [23.7] years; 12 611 women [53.6%]), 187 234 in the UKB cohort (mean [SD] age, 56.7 [8.1] years; 104 055 [55.6%] women), and 3242 in the HCR cohort (mean [SD] age, 52.5 [15.5] years; 2851 [87.9%] women). All 38 established gene-cancer associations were replicated, and 19 new associations were identified. These included the following 7 associations with neoplasms: CHEK2 with leukemia (odds ratio [OR], 3.81 [95% CI, 2.64-5.48]) and plasma cell neoplasms (OR, 3.12 [95% CI, 1.84-5.28]), ATM with gastric cancer (OR, 4.27 [95% CI, 2.35-7.44]) and pancreatic cancer (OR, 4.44 [95% CI, 2.66-7.40]), MUTYH (biallelic) with kidney cancer (OR, 32.28 [95% CI, 6.40-162.73]), MSH6 with bladder cancer (OR, 5.63 [95% CI, 2.75-11.49]), and APC with benign liver/intrahepatic bile duct tumors (OR, 52.01 [95% CI, 14.29-189.29]). The remaining 12 associations with nonneoplastic diseases included BRCA1/2 with ovarian cysts (OR, 3.15 [95% CI, 2.22-4.46] and 3.12 [95% CI, 2.36-4.12], respectively), MEN1 with acute pancreatitis (OR, 33.45 [95% CI, 9.25-121.02]), APC with gastritis and duodenitis (OR, 4.66 [95% CI, 2.61-8.33]), and PTEN with chronic gastritis (OR, 15.68 [95% CI, 6.01-40.92]). Conclusions and Relevance: The findings of this genetic association study analyzing the EHRs of 3 large cohorts suggest that these new phenotypes associated with hereditary cancer genes may facilitate early detection and better management of cancers. This study highlights the potential benefits of using EHR data in genomic medicine.

Mass Spectrometry of Au10(4-tert-butylbenzenethiolate)10 Nanoclusters Using Superconducting Tunnel Junction Cryodetection Reveals Distinct Metastable Fragmentation.

Cryodetection mass spectrometry (MS) was used to study the Au10(TBBT)10 (TBBT = 4-tert-butylbenzenethiolate) catenane nanocluster. The matrix-assisted laser desorption ionization (MALDI) process generates distinct fragments that can be arranged into two distinct regimes: (i) in-source fragmentation, which occurs rapidly in a relatively short (<170 ns) time frame, and (ii) metastable fragmentation, which occurs postacceleration during a time-of-flight (TOF) mass analysis over a longer time frame (>170 ns-250 µs). Using MALDI-TOF MS with superconducting tunnel junction (STJ) cryodetection, distinct metastable nanocluster fragments were resolved at lower energies deposited into the detector. The results also demonstrated that STJ cryodetection MS can be used to acquire multiple (>10), simultaneous tandem mass spectra in a single experiment. Simulated fragmentation of the Au10 nanocluster using ab initio molecular dynamics (AIMD) revealed the different fragmentation processes and confirmed the MS results. Using both the empirical MS data and AIMD calculations, fragmentation pathways are proposed for Au10(TBBT)10, which terminate with two small, stable ringed species.

Evaluation of pathogenetic mutations in breast cancer predisposition genes in population-based studies conducted among Chinese women.

PURPOSE: Limited studies have been conducted to evaluate pathogenetic mutations in breast cancer predisposition genes among Chinese women. To fully characterize germline mutations of these genes in this population, we used the whole-exome sequencing data in a population-based case-control study conducted in Shanghai, China. METHODS: We evaluated exonic, splicing, and copy number variants in 11 established and 14 candidate breast cancer predisposition genes in 831 invasive breast cancer cases and 839 controls. We identified 55 pathogenic variants, including 15 newly identified in this study. RESULTS: Approximately 8% of the cases and 0.6% of the cancer-free controls carried these pathogenetic variants (P = 3.05 × 10-15). Among cases, 3.7% had a BRCA2 pathogenic variant and 1.6% had a BRCA1 pathogenic variant, while 2.5% had a pathogenic variant in other genes including ATM, CHEK2, NBN, NF1, CDH1, PALB2, PTEN, TP53 as well as BARD1, BRIP, and RAD51D. Patients with BRCA1/2 pathogenic variants were more likely to have a family history of breast cancer and hormone receptor negative tumors compared with patients without pathogenic variants. CONCLUSIONS: This study highlighted the importance of hereditary breast cancer genes in the breast cancer etiology in this understudied population. Together with previous studies in East Asian women, this study suggested a relatively more prominent role of BRCA2 compared to BRCA1. This study also provides additional evidence to design cost-efficient genetic testing among Chinese women for risk assessment and early detection of breast cancer.

Discovery of rare coding variants in OGDHL and BRCA2 in relation to breast cancer risk in Chinese women.

The missing heritability of breast cancer could be partially attributed to rare variants (MAF < 0.5%). To identify breast cancer-associated rare coding variants, we conducted whole-exome sequencing (~50×) in genomic DNA samples obtained from 831 breast cancer cases and 839 controls of Chinese females. Using burden tests for each gene that included rare missense or predicted deleterious variants, we identified 29 genes showing promising associations with breast cancer risk. We replicated the association for two genes, OGDHL and BRCA2, at a Bonferroni-corrected p < 0.05, by genotyping an independent set of samples from 1,628 breast cancer cases and 1,943 controls. The association for OGDHL was primarily driven by three predicted deleterious variants (p.Val827Met, p.Pro839Leu, p.Phe836Ser; p < 0.01 for all). For BRCA2, we characterized a total of 27 disruptive variants, including 18 nonsense, six frameshift and three splicing variants, whereas they were only detected in cases, but none of the controls. All of these variants were either very rare (AF < 0.1%) or not detected in >4,500 East Asian women from the genome Aggregation database (gnomAD), providing additional support to our findings. Our study revealed a potential novel gene and multiple disruptive variants of BRCA2 for breast cancer risk, which may identify high-risk women in Chinese populations.

Three-Stage Evolution from Nonscalable to Scalable Optical Properties of Thiolate-Protected Gold Nanoclusters.

The evolution of the optical properties of gold nanoclusters (NCs) versus size is of great importance because it not only reveals the nature of quantum confinement in NCs, but also helps to understand how the molecular-like Au NCs transit to plasmonic nanoparticles. While some work has been done in studying the optical properties of NCs of certain individual sizes, the global picture remains unclear, such as the detailed relationship between size/structure and properties. Here, we investigate the grand evolution of the optical properties by comparing the steady-state absorption, bandgap, transient absorption, as well as carrier dynamics of a series of thiolate-protected gold NCs ranging from tens to hundreds of gold atoms. We find that, on the basis of their optical behaviors, gold NCs can be classified into three groups: (i) ultrasmall NCs (ca. <50 Au atoms) are nonscalable as their optical properties are strongly dependent on the structure rather than size; (ii) medium-sized NCs (about 50-100 Au atoms) show both size- and structure-dependent optical properties; and (iii) large-sized gold NCs (ca. >100 Au atoms) exhibit optical properties solely dependent on size, and the structure effect fades out. Unraveling the grand evolution from nonscalable to scalable optical properties and their mechanisms will greatly deepen scientific understanding of the nature of quantum-sized gold NCs and will also provide implications for plasmonic NPs.

Improving the phenotype risk score as a scalable approach to identifying patients with Mendelian disease.

OBJECTIVE: The Phenotype Risk Score (PheRS) is a method to detect Mendelian disease patterns using phenotypes from the electronic health record (EHR). We compared the performance of different approaches mapping EHR phenotypes to Mendelian disease features. MATERIALS AND METHODS: PheRS utilizes Mendelian diseases descriptions annotated with Human Phenotype Ontology (HPO) terms. In previous work, we presented a map linking phecodes (based on International Classification of Diseases [ICD]-Ninth Revision) to HPO terms. For this study, we integrated ICD-Tenth Revision codes and lab data. We also created a new map between HPO terms using customized groupings of ICD codes. We compared the performance with cases and controls for 16 Mendelian diseases using 2.5 million de-identified medical records. RESULTS: PheRS effectively distinguished cases from controls for all 15 positive controls and all approaches tested (P < 4 × 1016). Adding lab data led to a statistically significant improvement for 4 of 14 diseases. The custom ICD groupings improved specificity, leading to an average 8% increase for precision at 100 (-2% to 22%). Eight of 10 adults with cystic fibrosis tested had PheRS in the 95th percentile prio to diagnosis. DISCUSSION: Both phecodes and custom ICD groupings were able to detect differences between affected cases and controls at the population level. The ICD map showed better precision for the highest scoring individuals. Adding lab data improved performance at detecting population-level differences. CONCLUSIONS: PheRS is a scalable method to study Mendelian disease at the population level using electronic health record data and can potentially be used to find patients with undiagnosed Mendelian disease.

General Synthetic Route to High-Quality Colloidal III-V Semiconductor Quantum Dots Based on Pnictogen Chlorides.

The synthesis of colloidal III-V quantum dots (QDs), particularly of the arsenides and antimonides, has been limited by the lack of stable and available group V precursors. In this work, we exploit accessible InCl3- and pnictogen chloride-oleylamine as precursors to synthesize III-V QDs. Through coreduction reactions of the precursors, we achieve size- and stoichiometry-tunable binary InAs and InSb as well as ternary alloy InAs1-xSbx QDs. On the basis of structural, analytical, optical, and electrical characterization of the QDs and their thin-film assemblies, we study the effects of alloying on their particle formation and optoelectronic properties. We introduce a hydrazine-free hybrid ligand-exchange process to improve carrier transport in III-V QD thin films and realize InAs QD field-effect transistors with electron mobility > 5 cm2/(V s). We demonstrate that III-V QD thin films are promising candidate materials for infrared devices and show InAs1-xSbx QD photoconductors with superior short-wavelength infrared (SWIR) photoresponse than those of the binary QD devices.

Gold Nanoclusters: Bridging Gold Complexes and Plasmonic Nanoparticles in Photophysical Properties.

Recent advances in the determination of crystal structures and studies of optical properties of gold nanoclusters in the size range from tens to hundreds of gold atoms have started to reveal the grand evolution from gold complexes to nanoclusters and further to plasmonic nanoparticles. However, a detailed comparison of their photophysical properties is still lacking. Here, we compared the excited state behaviors of gold complexes, nanolcusters, and plasmonic nanoparticles, as well as small organic molecules by choosing four typical examples including the Au10 complex, Au25 nanocluster (1 nm metal core), 13 diameter Au nanoparticles, and Rhodamine B. To compare their photophysical behaviors, we performed steady-state absorption, photoluminescence, and femtosecond transient absorption spectroscopic measurements. It was found that gold nanoclusters behave somewhat like small molecules, showing both rapid internal conversion (<1 ps) and long-lived excited state lifetime (about 100 ns). Unlike the nanocluster form in which metal-metal transitions dominate, gold complexes showed significant charge transfer between metal atoms and surface ligands. Plasmonic gold nanoparticles, on the other hand, had electrons being heated and cooled (~100 ps time scale) after photo-excitation, and the relaxation was dominated by electron-electron scattering, electron-phonon coupling, and energy dissipation. In both nanoclusters and plasmonic nanoparticles, one can observe coherent oscillations of the metal core, but with different fundamental origins. Overall, this work provides some benchmarking features for organic dye molecules, organometallic complexes, metal nanoclusters, and plasmonic nanoparticles.

Discovery of a Pathogenic Variant rs139379666 (p. P2974L) in ATM for Breast Cancer Risk in Chinese Populations.

BACKGROUND: Pathogenic variants in susceptibility genes lead to increased breast cancer risk. METHODS: To identify coding variants associated with breast cancer risk, we conducted whole-exome sequencing in genomic DNA samples from 831 breast cancer cases and 839 controls of Chinese women. We also genotyped samples, including 4,580 breast cancer cases and 6,695 controls, using whole exome-chip arrays. We further performed a replication study using a Multi-Ethnic Global Array in samples from 1,793 breast cases and 2,059 controls. A single marker analysis was performed using the Fisher exact test. RESULTS: We identified a missense variant (rs139379666, P2974L; AF = 0.09% for breast cancer cases, but none for controls) in the ATM gene for breast cancer risk using combing data from 7,204 breast cancer cases and 9,593 controls (P = 1.7 × 10-5). To investigate the functionality of the variant, we first silenced ATM and then transfected the overexpression vectors of ATM containing the risk alleles (TT) or reference alleles (CC) of the variant in U2OS and breast cancer SK-BR3 cells, respectively. Our results showed that compared with the reference allele, the risk allele significantly disrupts the activity of homologous recombination-mediated double-strand breaks repair efficiency. Our results further showed that the risk allele may play a defected regulation role in the activity of the ATM structure. CONCLUSIONS: Our findings identified a novel mutation that disrupts ATM function, conferring to breast cancer risk. IMPACT: Functional investigation of genetic association findings is necessary to discover a pathogenic variant for breast cancer risk.

Controlling magnetism of Au133(TBBT)52 nanoclusters at single electron level and implication for nonmetal to metal transition.

The transition from the discrete, excitonic state to the continuous, metallic state in thiolate-protected gold nanoclusters is of fundamental interest and has attracted significant efforts in recent research. Compared with optical and electronic transition behavior, the transition in magnetism from the atomic gold paramagnetism (Au 6s1) to the band behavior is less studied. In this work, the magnetic properties of 1.7 nm [Au133(TBBT)52]0 nanoclusters (where TBBT = 4-tert-butylbenzenethiolate) with 81 nominal "valence electrons" are investigated by electron paramagnetic resonance (EPR) spectroscopy. Quantitative EPR analysis shows that each cluster possesses one unpaired electron (spin), indicating that the electrons fill into discrete orbitals instead of a continuous band, for that one electron in the band would give a much smaller magnetic moment. Therefore, [Au133(TBBT)52]0 possesses a nonmetallic electronic structure. Furthermore, we demonstrate that the unpaired spin can be removed by oxidizing [Au133(TBBT)52]0 to [Au133(TBBT)52]+ and the nanocluster transforms from paramagnetism to diamagnetism accordingly. The UV-vis absorption spectra remain the same in the process of single-electron loss or addition. Nuclear magnetic resonance (NMR) is applied to probe the charge and magnetic states of Au133(TBBT)52, and the chemical shifts of 52 surface TBBT ligands are found to be affected by the spin in the gold core. The NMR spectrum of Au133(TBBT)52 shows a 13-fold splitting with 4-fold degeneracy of 52 TBBT ligands, which are correlated to the quasi-D 2 symmetry of the ligand shell. Overall, this work provides important insights into the electronic structure of Au133(TBBT)52 by combining EPR, optical and NMR studies, which will pave the way for further understanding of the transition behavior in metal nanoclusters.

Large-Scale Genome-Wide Association Study of East Asians Identifies Loci Associated With Risk for Colorectal Cancer.

BACKGROUND & AIMS: Genome-wide association studies (GWASs) have associated approximately 50 loci with risk of colorectal cancer (CRC)-nearly one third of these loci were initially associated with CRC in studies conducted in East Asian populations. We conducted a GWAS of East Asians to identify CRC risk loci and evaluate the generalizability of findings from GWASs of European populations to Asian populations. METHODS: We analyzed genetic data from 22,775 patients with CRC (cases) and 47,731 individuals without cancer (controls) from 14 studies in the Asia Colorectal Cancer Consortium. First, we performed a meta-analysis of 7 GWASs (10,625 cases and 34,595 controls) and identified 46,554 promising risk variants for replication by adding them to the Multi-Ethnic Global Array (MEGA) for genotype analysis in 6445 cases and 7175 controls. These data were analyzed, along with data from an additional 5705 cases and 5961 controls genotyped using the OncoArray. We also obtained data from 57,976 cases and 67,242 controls of European descent. Variants at identified risk loci were functionally annotated and evaluated in correlation with gene expression levels. RESULTS: A meta-analyses of all samples from people of Asian descent identified 13 loci and 1 new variant at a known locus (10q24.2) associated with risk of CRC at the genome-wide significance level of P < 5 × 10-8. We did not perform experiments to replicate these associations in additional individuals of Asian ancestry. However, the lead risk variant in 6 of these loci was also significantly associated with risk of CRC in European descendants. A strong association (44%-75% increase in risk per allele) was found for 2 low-frequency variants: rs201395236 at 1q44 (minor allele frequency, 1.34%) and rs77969132 at 12p11.21 (minor allele frequency, 1.53%). For 8 of the 13 associated loci, the variants with the highest levels of significant association were located inside or near the protein-coding genes L1TD1, EFCAB2, PPP1R21, SLCO2A1, HLA-G, NOTCH4, DENND5B, and GNAS. For other intergenic loci, we provided evidence for the possible involvement of the genes ALDH7A1, PRICKLE1, KLF5, WWOX, and GLP2R. We replicated findings for 41 of 52 previously reported risk loci. CONCLUSIONS: We showed that most of the risk loci previously associated with CRC risk in individuals of European descent were also associated with CRC risk in East Asians. Furthermore, we identified 13 loci significantly associated with risk for CRC in Asians. Many of these loci contained genes that regulate the immune response, Wnt signaling to ß-catenin, prostaglandin E2 catabolism, and cell pluripotency and proliferation. Further analyses of these genes and their variants is warranted, particularly for the 8 loci for which the lead CRC risk variants were not replicated in persons of European descent.