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Dive into the research topics where Kevin B. Jacobs is active.

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Featured researches published by Kevin B. Jacobs.


Nature Genetics | 2007

A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer

David J. Hunter; Peter Kraft; Kevin B. Jacobs; David G. Cox; Meredith Yeager; Susan E. Hankinson; Sholom Wacholder; Zhaoming Wang; Robert Welch; Amy Hutchinson; Junwen Wang; Kai Yu; Nilanjan Chatterjee; Nick Orr; Walter C. Willett; Graham A. Colditz; Regina G. Ziegler; Christine D. Berg; Saundra S. Buys; Catherine A. McCarty; Heather Spencer Feigelson; Eugenia E. Calle; Michael J. Thun; Richard B. Hayes; Margaret A. Tucker; Daniela S. Gerhard; Joseph F. Fraumeni; Robert N. Hoover; Gilles Thomas; Stephen J. Chanock

We conducted a genome-wide association study (GWAS) of breast cancer by genotyping 528,173 SNPs in 1,145 postmenopausal women of European ancestry with invasive breast cancer and 1,142 controls. We identified four SNPs in intron 2 of FGFR2 (which encodes a receptor tyrosine kinase and is amplified or overexpressed in some breast cancers) that were highly associated with breast cancer and confirmed this association in 1,776 affected individuals and 2,072 controls from three additional studies. Across the four studies, the association with all four SNPs was highly statistically significant (Ptrend for the most strongly associated SNP (rs1219648) = 1.1 × 10−10; population attributable risk = 16%). Four SNPs at other loci most strongly associated with breast cancer in the initial GWAS were not associated in the replication studies. Our summary results from the GWAS are available online in a form that should speed the identification of additional risk loci.


Nature Genetics | 2007

Genome-wide association study of prostate cancer identifies a second risk locus at 8q24.

Meredith Yeager; Nick Orr; Richard B. Hayes; Kevin B. Jacobs; Peter Kraft; Sholom Wacholder; Mark J Minichiello; Paul Fearnhead; Kai Yu; Nilanjan Chatterjee; Zhaoming Wang; Robert Welch; Brian Staats; Eugenia E. Calle; Heather Spencer Feigelson; Michael J. Thun; Carmen Rodriguez; Demetrius Albanes; Jarmo Virtamo; Stephanie J. Weinstein; Fredrick R. Schumacher; Edward Giovannucci; Walter C. Willett; Geraldine Cancel-Tassin; Olivier Cussenot; Antoine Valeri; Gerald L. Andriole; Edward P. Gelmann; Margaret A. Tucker; Daniela S. Gerhard

Recently, common variants on human chromosome 8q24 were found to be associated with prostate cancer risk. While conducting a genome-wide association study in the Cancer Genetic Markers of Susceptibility project with 550,000 SNPs in a nested case-control study (1,172 cases and 1,157 controls of European origin), we identified a new association at 8q24 with an independent effect on prostate cancer susceptibility. The most significant signal is 70 kb centromeric to the previously reported SNP, rs1447295, but shows little evidence of linkage disequilibrium with it. A combined analysis with four additional studies (total: 4,296 cases and 4,299 controls) confirms association with prostate cancer for rs6983267 in the centromeric locus (P = 9.42 × 10−13; heterozygote odds ratio (OR): 1.26, 95% confidence interval (c.i.): 1.13–1.41; homozygote OR: 1.58, 95% c.i.: 1.40–1.78). Each SNP remained significant in a joint analysis after adjusting for the other (rs1447295 P = 1.41 × 10−11; rs6983267 P = 6.62 × 10−10). These observations, combined with compelling evidence for a recombination hotspot between the two markers, indicate the presence of at least two independent loci within 8q24 that contribute to prostate cancer in men of European ancestry. We estimate that the population attributable risk of the new locus, marked by rs6983267, is higher than the locus marked by rs1447295 (21% versus 9%).


Nature Genetics | 2008

Multiple loci identified in a genome-wide association study of prostate cancer

Gilles Thomas; Kevin B. Jacobs; Meredith Yeager; Peter Kraft; Sholom Wacholder; Nick Orr; Kai Yu; Nilanjan Chatterjee; Robert Welch; Amy Hutchinson; Andrew Crenshaw; Geraldine Cancel-Tassin; Brian Staats; Zhaoming Wang; Jesus Gonzalez-Bosquet; Jun Fang; Xiang Deng; Sonja I. Berndt; Eugenia E. Calle; Heather Spencer Feigelson; Michael J. Thun; Carmen Rodriguez; Demetrius Albanes; Jarmo Virtamo; Stephanie J. Weinstein; Fredrick R. Schumacher; Edward Giovannucci; Walter C. Willett; Olivier Cussenot; Antoine Valeri

We followed our initial genome-wide association study (GWAS) of 527,869 SNPs on 1,172 individuals with prostate cancer and 1,157 controls of European origin—nested in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial prospective study—by testing 26,958 SNPs in four independent studies (total of 3,941 cases and 3,964 controls). In the combined joint analysis, we confirmed three previously reported loci (two independent SNPs at 8q24 and one in HNF1B (formerly known as TCF2 on 17q); P < 10−10). In addition, loci on chromosomes 7, 10 (two loci) and 11 were highly significant (between P < 7.31 × 10−13 and P < 2.14 × 10−6). Loci on chromosome 10 include MSMB, which encodes β-microseminoprotein, a primary constituent of semen and a proposed prostate cancer biomarker, and CTBP2, a gene with antiapoptotic activity; the locus on chromosome 7 is at JAZF1, a transcriptional repressor that is fused by chromosome translocation to SUZ12 in endometrial cancer. Of the nine loci that showed highly suggestive associations (P < 2.5 × 10−5), four best fit a recessive model and included candidate susceptibility genes: CPNE3, IL16 and CDH13. Our findings point to multiple loci with moderate effects associated with susceptibility to prostate cancer that, taken together, in the future may predict high risk in select individuals.


Nature Genetics | 2008

Identification of ten loci associated with height highlights new biological pathways in human growth

Guillaume Lettre; Anne U. Jackson; Christian Gieger; Fredrick R. Schumacher; Sonja I. Berndt; Serena Sanna; Susana Eyheramendy; Benjamin F. Voight; Johannah L. Butler; Candace Guiducci; Thomas Illig; Rachel Hackett; Iris M. Heid; Kevin B. Jacobs; Valeriya Lyssenko; Manuela Uda; Michael Boehnke; Stephen J. Chanock; Leif Groop; Frank B. Hu; Bo Isomaa; Peter Kraft; Leena Peltonen; Veikko Salomaa; David Schlessinger; David J. Hunter; Richard B. Hayes; Gonçalo R. Abecasis; H.-Erich Wichmann; Karen L. Mohlke

Height is a classic polygenic trait, reflecting the combined influence of multiple as-yet-undiscovered genetic factors. We carried out a meta-analysis of genome-wide association study data of height from 15,821 individuals at 2.2 million SNPs, and followed up the strongest findings in >10,000 subjects. Ten newly identified and two previously reported loci were strongly associated with variation in height (P values from 4 × 10−7 to 8 × 10−22). Together, these 12 loci account for ∼2% of the population variation in height. Individuals with ≤8 height-increasing alleles and ≥16 height-increasing alleles differ in height by ∼3.5 cm. The newly identified loci, along with several additional loci with strongly suggestive associations, encompass both strong biological candidates and unexpected genes, and highlight several pathways (let-7 targets, chromatin remodeling proteins and Hedgehog signaling) as important regulators of human stature. These results expand the picture of the biological regulation of human height and of the genetic architecture of this classical complex trait.


Nature Genetics | 2009

A multistage genome-wide association study in breast cancer identifies two new risk alleles at 1p11.2 and 14q24.1 (RAD51L1).

Gilles Thomas; Kevin B. Jacobs; Peter Kraft; Meredith Yeager; Sholom Wacholder; David G. Cox; Susan E. Hankinson; Amy Hutchinson; Zhaoming Wang; Kai Yu; Nilanjan Chatterjee; Montserrat Garcia-Closas; Jesus Gonzalez-Bosquet; Ludmila Prokunina-Olsson; Nick Orr; Walter C. Willett; Graham A. Colditz; Regina G. Ziegler; Christine D. Berg; Saundra S. Buys; Catherine A. McCarty; Heather Spencer Feigelson; Eugenia E. Calle; Michael J. Thun; Ryan Diver; Ross L. Prentice; Rebecca D. Jackson; Charles Kooperberg; Rowan T. Chlebowski; Jolanta Lissowska

We conducted a three-stage genome-wide association study (GWAS) of breast cancer in 9,770 cases and 10,799 controls in the Cancer Genetic Markers of Susceptibility (CGEMS) initiative. In stage 1, we genotyped 528,173 SNPs in 1,145 cases of invasive breast cancer and 1,142 controls. In stage 2, we analyzed 24,909 top SNPs in 4,547 cases and 4,434 controls. In stage 3, we investigated 21 loci in 4,078 cases and 5,223 controls. Two new loci achieved genome-wide significance. A pericentromeric SNP on chromosome 1p11.2 (rs11249433; P = 6.74 × 10−10 adjusted genotype test, 2 degrees of freedom) resides in a large linkage disequilibrium block neighboring NOTCH2 and FCGR1B; this signal was stronger for estrogen-receptor–positive tumors. A second SNP on chromosome 14q24.1 (rs999737; P = 1.74 × 10−7) localizes to RAD51L1, a gene in the homologous recombination DNA repair pathway. We also confirmed associations with loci on chromosomes 2q35, 5p12, 5q11.2, 8q24, 10q26 and 16q12.1.


Nature Genetics | 2010

Estimation of effect size distribution from genome-wide association studies and implications for future discoveries

Ju Hyun Park; Sholom Wacholder; Mitchell H. Gail; Ulrike Peters; Kevin B. Jacobs; Stephen J. Chanock; Nilanjan Chatterjee

We report a set of tools to estimate the number of susceptibility loci and the distribution of their effect sizes for a trait on the basis of discoveries from existing genome-wide association studies (GWASs). We propose statistical power calculations for future GWASs using estimated distributions of effect sizes. Using reported GWAS findings for height, Crohns disease and breast, prostate and colorectal (BPC) cancers, we determine that each of these traits is likely to harbor additional loci within the spectrum of low-penetrance common variants. These loci, which can be identified from sufficiently powerful GWASs, together could explain at least 15–20% of the known heritability of these traits. However, for BPC cancers, which have modest familial aggregation, our analysis suggests that risk models based on common variants alone will have modest discriminatory power (63.5% area under curve), even with new discoveries.


American Journal of Human Genetics | 2009

A Genome-wide Association Study of Lung Cancer Identifies a Region of Chromosome 5p15 Associated with Risk for Adenocarcinoma

Maria Teresa Landi; Nilanjan Chatterjee; Kai Yu; Lynn R. Goldin; Alisa M. Goldstein; Melissa Rotunno; Lisa Mirabello; Kevin B. Jacobs; William Wheeler; Meredith Yeager; Andrew W. Bergen; Qizhai Li; Dario Consonni; Angela Cecilia Pesatori; Sholom Wacholder; Michael J. Thun; Ryan Diver; Martin M. Oken; Jarmo Virtamo; Demetrius Albanes; Zhaoming Wang; Laurie Burdette; Kimberly F. Doheny; Elizabeth W. Pugh; Cathy C. Laurie; Paul Brennan; Rayjean J. Hung; Valerie Gaborieau; James D. McKay; Mark Lathrop

Three genetic loci for lung cancer risk have been identified by genome-wide association studies (GWAS), but inherited susceptibility to specific histologic types of lung cancer is not well established. We conducted a GWAS of lung cancer and its major histologic types, genotyping 515,922 single-nucleotide polymorphisms (SNPs) in 5739 lung cancer cases and 5848 controls from one population-based case-control study and three cohort studies. Results were combined with summary data from ten additional studies, for a total of 13,300 cases and 19,666 controls of European descent. Four studies also provided histology data for replication, resulting in 3333 adenocarcinomas (AD), 2589 squamous cell carcinomas (SQ), and 1418 small cell carcinomas (SC). In analyses by histology, rs2736100 (TERT), on chromosome 5p15.33, was associated with risk of adenocarcinoma (odds ratio [OR]=1.23, 95% confidence interval [CI]=1.13-1.33, p=3.02x10(-7)), but not with other histologic types (OR=1.01, p=0.84 and OR=1.00, p=0.93 for SQ and SC, respectively). This finding was confirmed in each replication study and overall meta-analysis (OR=1.24, 95% CI=1.17-1.31, p=3.74x10(-14) for AD; OR=0.99, p=0.69 and OR=0.97, p=0.48 for SQ and SC, respectively). Other previously reported association signals on 15q25 and 6p21 were also refined, but no additional loci reached genome-wide significance. In conclusion, a lung cancer GWAS identified a distinct hereditary contribution to adenocarcinoma.


Nature Genetics | 2009

Genome-wide association study identifies variants in the ABO locus associated with susceptibility to pancreatic cancer

Laufey Amundadottir; Peter Kraft; Rachael Z. Stolzenberg-Solomon; Charles S. Fuchs; Gloria M. Petersen; Alan A. Arslan; H. Bas Bueno-de-Mesquita; Myron D. Gross; Kathy J. Helzlsouer; Eric J. Jacobs; Andrea Z. LaCroix; Wei Zheng; Demetrius Albanes; William R. Bamlet; Christine D. Berg; Franco Berrino; Sheila Bingham; Julie E. Buring; Paige M. Bracci; Federico Canzian; Françoise Clavel-Chapelon; Sandra Clipp; Michelle Cotterchio; Mariza de Andrade; Eric J. Duell; John W. Fox; Steven Gallinger; J. Michael Gaziano; Edward Giovannucci; Michael Goggins

We conducted a two-stage genome-wide association study of pancreatic cancer, a cancer with one of the lowest survival rates worldwide. We genotyped 558,542 SNPs in 1,896 individuals with pancreatic cancer and 1,939 controls drawn from 12 prospective cohorts plus one hospital-based case-control study. We conducted a combined analysis of these groups plus an additional 2,457 affected individuals and 2,654 controls from eight case-control studies, adjusting for study, sex, ancestry and five principal components. We identified an association between a locus on 9q34 and pancreatic cancer marked by the SNP rs505922 (combined P = 5.37 × 10−8; multiplicative per-allele odds ratio 1.20; 95% confidence interval 1.12–1.28). This SNP maps to the first intron of the ABO blood group gene. Our results are consistent with earlier epidemiologic evidence suggesting that people with blood group O may have a lower risk of pancreatic cancer than those with groups A or B.


WOS | 2013

Genome-wide association study of circulating vitamin D levels

Jiyoung Ahn; Kai Yu; Rachael Z. Stolzenberg-Solomon; K. Claire Simon; Marjorie L. McCullough; Lisa Gallicchio; Eric J. Jacobs; Alberto Ascherio; Kathy J. Helzlsouer; Kevin B. Jacobs; Qizhai Li; Stephanie J. Weinstein; Mark P. Purdue; Jarmo Virtamo; Ronald L. Horst; William Wheeler; Stephen J. Chanock; David J. Hunter; Richard B. Hayes; Peter Kraft; Demetrius Albanes

The primary circulating form of vitamin D, 25-hydroxy-vitamin D [25(OH)D], is associated with multiple medical outcomes, including rickets, osteoporosis, multiple sclerosis and cancer. In a genome-wide association study (GWAS) of 4501 persons of European ancestry drawn from five cohorts, we identified single-nucleotide polymorphisms (SNPs) in the gene encoding group-specific component (vitamin D binding) protein, GC, on chromosome 4q12-13 that were associated with 25(OH)D concentrations: rs2282679 (P = 2.0 × 10−30), in linkage disequilibrium (LD) with rs7041, a non-synonymous SNP (D432E; P = 4.1 × 10−22) and rs1155563 (P = 3.8 × 10−25). Suggestive signals for association with 25(OH)D were also observed for SNPs in or near three other genes involved in vitamin D synthesis or activation: rs3829251 on chromosome 11q13.4 in NADSYN1 [encoding nicotinamide adenine dinucleotide (NAD) synthetase; P = 8.8 × 10−7], which was in high LD with rs1790349, located in DHCR7, the gene encoding 7-dehydrocholesterol reductase that synthesizes cholesterol from 7-dehydrocholesterol; rs6599638 in the region harboring the open-reading frame 88 (C10orf88) on chromosome 10q26.13 in the vicinity of ACADSB (acyl-Coenzyme A dehydrogenase), involved in cholesterol and vitamin D synthesis (P = 3.3 × 10−7); and rs2060793 on chromosome 11p15.2 in CYP2R1 (cytochrome P450, family 2, subfamily R, polypeptide 1, encoding a key C-25 hydroxylase that converts vitamin D3 to an active vitamin D receptor ligand; P = 1.4 × 10−5). We genotyped SNPs in these four regions in 2221 additional samples and confirmed strong genome-wide significant associations with 25(OH)D through meta-analysis with the GWAS data for GC (P = 1.8 × 10−49), NADSYN1/DHCR7 (P = 3.4 × 10−9) and CYP2R1 (P = 2.9 × 10−17), but not C10orf88 (P = 2.4 × 10−5).


The New England Journal of Medicine | 2010

Performance of common genetic variants in breast-cancer risk models.

Sholom Wacholder; Patricia Hartge; Ross L. Prentice; Montserrat Garcia-Closas; Heather Spencer Feigelson; W. Ryan Diver; Michael J. Thun; David G. Cox; Susan E. Hankinson; Peter Kraft; Bernard Rosner; Christine D. Berg; Louise A. Brinton; Jolanta Lissowska; Mark E. Sherman; Rowan T. Chlebowski; Charles Kooperberg; Rebecca D. Jackson; Dennis W. Buckman; Peter Hui; Ruth M. Pfeiffer; Kevin B. Jacobs; Gilles Thomas; Robert N. Hoover; Mitchell H. Gail; Stephen J. Chanock; David J. Hunter

BACKGROUND Genomewide association studies have identified multiple genetic variants associated with breast cancer. The extent to which these variants add to existing risk-assessment models is unknown. METHODS We used information on traditional risk factors and 10 common genetic variants associated with breast cancer in 5590 case subjects and 5998 control subjects, 50 to 79 years of age, from four U.S. cohort studies and one case-control study from Poland to fit models of the absolute risk of breast cancer. With the use of receiver-operating-characteristic curve analysis, we calculated the area under the curve (AUC) as a measure of discrimination. By definition, random classification of case and control subjects provides an AUC of 50%; perfect classification provides an AUC of 100%. We calculated the fraction of case subjects in quintiles of estimated absolute risk after the addition of genetic variants to the traditional risk model. RESULTS The AUC for a risk model with age, study and entry year, and four traditional risk factors was 58.0%; with the addition of 10 genetic variants, the AUC was 61.8%. About half the case subjects (47.2%) were in the same quintile of risk as in a model without genetic variants; 32.5% were in a higher quintile, and 20.4% were in a lower quintile. CONCLUSIONS The inclusion of newly discovered genetic factors modestly improved the performance of risk models for breast cancer. The level of predicted breast-cancer risk among most women changed little after the addition of currently available genetic information.

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Stephen J. Chanock

National Institutes of Health

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Meredith Yeager

National Institutes of Health

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Demetrius Albanes

National Institutes of Health

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Amy Hutchinson

Brigham and Women's Hospital

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Nilanjan Chatterjee

National Institutes of Health

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Zhaoming Wang

National Institutes of Health

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David J. Hunter

Royal North Shore Hospital

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Robert N. Hoover

United States Department of Health and Human Services

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