Factors affecting plant community composition and dynamics in the Ossipee Pine Barrens, New Hampshire

Forty-one 0.25 ha sites were sampled in the Ossipee Pine Barrens to identify and describe tree community types and investigate factors controlling forest composition and dynamics. Every site had three site-time assemblages (STA\u27s) representing past, present, and future trees. Past (1952) vegetation was calculated based on reverse growth estimates of current stems and stumps. Future (2052) vegetation was predicted by current sapling (\u3c10 cm dbh and ≥1 m tall) relative densities. Cluster analysis produced three community types from 121 STA\u27s: pitch pine, mixed pine-hardwoods, and red maple. Pitch pine communities comprised 63% of sites in 1952, but declined since. Mixed pine-hardwoods peaked at 58% in 2002, but were predicted to decline to 37% by 2052 as sites transitioned to red maple. The red maple community only appeared in the future after current saplings replaced aging pitch pine canopies, but the type was predicted to comprise 50% of sites by 2052. Assuming continued fire suppression, pitch pine communities will retain only 12% of sites by 2052. Control over vegetation patterns and successional dynamics by (1) soils, (2) seed source, and (3) disturbance was investigated using field evidence, accounts from residents and forest managers, and dendrochronology. Factors affecting forests since stand formation were analyzed individually and with multivariate techniques. Seed source variables explained the greatest amount of variation in vegetation, followed closely by fire-related disturbance variables and weakly by soil texture. Logging disturbance and soil nutrients were not significant predictors of vegetation in the Ossipee Pine Barrens

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Detectable clonal mosaicism and its relationship to aging and cancer

In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of >2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 × 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 × 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases

Detectable clonal mosaicism and its relationship to aging and cancer

In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of &gt; 2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 x 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 x 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases

Detectable clonal mosaicism and its relationship to aging and cancer

10.1038/ng.2270Nature Genetics446651-658NGEN

Characterization of large structural genetic mosaicism in human autosomes

Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.Some individuals, studies, and centers received individual support. The grant numbers are: Addiction (U01HG004422, NIAAA: U10AA008401, NCI: P01CA089392, NIDA: R01DA013423, R01DA019963); Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (U.S. Public Health Service contracts: N01-CN-45165, N01-RC-45035, N01-RC-37004, NCI contract: HHSN261201000006C); Birth weight (U01HG004415); Blood clotting (R37 HL 039693); Broad Center for Genotyping and Analysis (U01HG04424); Cancer Prevention Study-II (American Cancer Society); Center for Inherited Disease Research (U01HG004438, HHSN268200782096C); Cleft lip/palate (NIDCR: U01DE018993 and R01DE016148, NIH contract: HHSN268200782096C); Dental Caries (NIDCR:U01DE018903 and R01DE014899, NIH CIDR contract: HHSN268200-782096C); Endometrial cancer (R01 CA134958); Fudan Lung Cancer Study (Ministry of Health (201002007); Ministry of Science and Technology (2011BAI09B00); National S&T Major Special Project (2011ZX09102-010-01); China National High-Tech Research and Development Program (2012AA02A517, 2012AA02A518); National Science Foundation of China (30890034); National Basic Research Program (2012CB944600); Scientific and Technological Support Plans from Jiangsu Province (BE2010715)); Gene-Environment Association Studies (Coordinating Center :U01 HG004446, Manuscript preparation: P01-GM099568); Genes and Environment in Lung Cancer, Singapore Study (National Medical Research Council Singapore grant (NMRC/0897/2004, NMRC/1075/2006); Agency for Science, Technology and Research (A*STAR) of Singapore); Genetic Epidemiological Study of Lung Adenocarcinoma (National Research Program on Genomic Medicine in Taiwan (DOH98-TD-G-111-015); National Research Program for Biopharmaceuticals in Taiwan (DOH 100-TD-PB-111-TM013); National Science Council,Taiwan (NSC 100-2319-B-400-001)); Glaucoma (NHGRI: U01HG004728, NEI: R01EY015473, NEI: R01EY015872, Harvard Medical School Distinguished Ophthalmology Scholar Award: Louis Pasquale); Guangdong Study (Foundation of Guangdong Science and Technology Department (2006B60101010, 2007A032000002, 2011A030400010); Guangzhou Science and Information Technology Bureau (2011Y2-00014); Chinese Lung Cancer Research Foundation; National Natural Science Foundation of China (81101549); Natural Science Foundation of Guangdong Province (S2011010000792)); Health Professionals Follow-up Study (UM1 CA167552, R01 HL35464); Hong Kong Study (General Research Fund of Research Grant Council, Hong Kong (781511M)); Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH; Intramural Research Program of the NIH, National Library of Medicine; Intramural Research Program of the National Institute for Occupational Safety and Health; Japanese Female Lung Cancer Collaborative Study (Grants-in-Aid from the Ministry of Health, Labor, and Welfare for Research on Applying Health Technology and for the 3rd-term Comprehensive 10-year Strategy for Cancer Control; National Cancer Center Research and Development Fund; Grant-in-Aid for Scientific Research on Priority Areas and on Innovative Area from the Ministry of Education, Science, Sports, Culture and Technology of Japan; NCI (R01-CA121210)); Lung cancer (Z01CP010200); Lung health (U01HG004738); Ministry of Health (201002007); Ministry of Science and Technology (2011BAI09B00); Melanoma (NCI R29CA70334, R01CA100264, P50CA093459); NLCS (China National High-Tech Research and Development Program Grant (2009AA022705); Priority Academic Program Development of Jiangsu Higher Education Institution; National Key Basic Research Program Grant (2011CB503805)); Nurses’ Health Study (P01 CA87969, R01 CA49449); Nurses’ Health Study II (UM1 CA176726, R01, 67262); OpPancreatic cancer (Mayo Clinic SPORE in Pancreatic Cancer: P50CA102701); Prematurity (U01HG004423); Prostate cancer (U01HG004726, NCI: CA63464, CA54281, CA1326792, RC2 CA148085); Shanghai Women’s Health Cohort Study (National Institutes of Health (R37 CA70867); National Cancer Institute intramural research program; NCI Intramural Research Program contract (N02 CP1101066)); Shenyang Lung Cancer Study (National Nature Science Foundation of China (81102194); Liaoning Provincial Department of Education (LS2010168); China Medical Board (00726)); Singapore Chinese Health Study (NIH grants: NCI R01 CA55069, R35 CA53890, R01 CA80205, and R01 CA144034); South Korea Multi-Center Lung Cancer Study (National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (2011-0016106); National R&D Program for Cancer Control, Ministry of Health &Welfare, Republic of Korea (0720550-2); (A010250)); Tianjin Lung Cancer Study (Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT); China (IRT1076), Tianjin Cancer Institute and Hospital, National Foundation for Cancer Research US); Venous thromboembolism (U01HG004735); Wuhan lung cancer study (National Key Basic Research and Development Program (2011CB503800)) and Yunnan Lung Cancer Study (Intramural program of U.S. National Institutes of Health; National Cancer Institute). Additionally, K.C.B. was supported in part by the Mary Beryl Patch Turnbull Scholar Program. The GENEVA consortium thanks the participants and the staff of all GENEVA studies for their important contributions. Support for the GENEVA genome-wide association studies was provided through the NIH Genes, Environment and Health Initiative (GEI)

Detectable clonal mosaicism and its relationship to aging and cancer

In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of >2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 × 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 × 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases

Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for Thirteen Cancer Types

BACKGROUND: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. METHODS: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. RESULTS: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. CONCLUSION: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation

Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for Thirteen Cancer Types

BACKGROUND: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. METHODS: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. RESULTS: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. CONCLUSION: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation

Analysis of heritability and shared heritability based on genome-wide association studies for 13 cancer types

Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl², on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.11 page(s