Author: "Joshi AD" - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Joshi AD"' showing total 318 results

Start Over Author "Joshi AD"

318 results on '"Joshi AD"'

1. Genetic risk impacts the association of menopausal hormone therapy with colorectal cancer risk

Author: Tian, Y, Lin, Y, Qu, C, Arndt, V, Baurley, JW, Berndt, SI, Bien, SA, Bishop, DT, Brenner, H, Buchanan, DD, Budiarto, A, Campbell, PT, Carreras-Torres, R, Casey, G, Chan, AT, Chen, R, Chen, X, Conti, DV, Diez-Obrero, V, Dimou, N, Drew, DA, Figueiredo, JC, Gallinger, S, Giles, GG, Gruber, SB, Gunter, MJ, Harlid, S, Harrison, TA, Hidaka, A, Hoffmeister, M, Huyghe, JR, Jenkins, MA, Jordahl, KM, Joshi, AD, Keku, TO, Kawaguchi, E, Kim, AE, Kundaje, A, Larsson, SC, Marchand, LL, Lewinger, JP, Li, L, Moreno, V, Morrison, J, Murphy, N, Nan, H, Nassir, R, Newcomb, PA, Obon-Santacana, M, Ogino, S, Ose, J, Pardamean, B, Pellatt, AJ, Peoples, AR, Platz, EA, Potter, JD, Prentice, RL, Rennert, G, Ruiz-Narvaez, EA, Sakoda, LC, Schoen, RE, Shcherbina, A, Stern, MC, Su, Y-R, Thibodeau, SN, Thomas, DC, Tsilidis, KK, van Duijnhoven, FJB, Van Guelpen, B, Visvanathan, K, White, E, Wolk, A, Woods, MO, Wu, AH, Peters, U, Gauderman, WJ, Hsu, L, Chang-Claude, J, Tian, Y, Lin, Y, Qu, C, Arndt, V, Baurley, JW, Berndt, SI, Bien, SA, Bishop, DT, Brenner, H, Buchanan, DD, Budiarto, A, Campbell, PT, Carreras-Torres, R, Casey, G, Chan, AT, Chen, R, Chen, X, Conti, DV, Diez-Obrero, V, Dimou, N, Drew, DA, Figueiredo, JC, Gallinger, S, Giles, GG, Gruber, SB, Gunter, MJ, Harlid, S, Harrison, TA, Hidaka, A, Hoffmeister, M, Huyghe, JR, Jenkins, MA, Jordahl, KM, Joshi, AD, Keku, TO, Kawaguchi, E, Kim, AE, Kundaje, A, Larsson, SC, Marchand, LL, Lewinger, JP, Li, L, Moreno, V, Morrison, J, Murphy, N, Nan, H, Nassir, R, Newcomb, PA, Obon-Santacana, M, Ogino, S, Ose, J, Pardamean, B, Pellatt, AJ, Peoples, AR, Platz, EA, Potter, JD, Prentice, RL, Rennert, G, Ruiz-Narvaez, EA, Sakoda, LC, Schoen, RE, Shcherbina, A, Stern, MC, Su, Y-R, Thibodeau, SN, Thomas, DC, Tsilidis, KK, van Duijnhoven, FJB, Van Guelpen, B, Visvanathan, K, White, E, Wolk, A, Woods, MO, Wu, AH, Peters, U, Gauderman, WJ, Hsu, L, and Chang-Claude, J
Abstract: BACKGROUND: Menopausal hormone therapy (MHT), a common treatment to relieve symptoms of menopause, is associated with a lower risk of colorectal cancer (CRC). To inform CRC risk prediction and MHT risk-benefit assessment, we aimed to evaluate the joint association of a polygenic risk score (PRS) for CRC and MHT on CRC risk. METHODS: We used data from 28,486 postmenopausal women (11,519 cases and 16,967 controls) of European descent. A PRS based on 141 CRC-associated genetic variants was modeled as a categorical variable in quartiles. Multiplicative interaction between PRS and MHT use was evaluated using logistic regression. Additive interaction was measured using the relative excess risk due to interaction (RERI). 30-year cumulative risks of CRC for 50-year-old women according to MHT use and PRS were calculated. RESULTS: The reduction in odds ratios by MHT use was larger in women within the highest quartile of PRS compared to that in women within the lowest quartile of PRS (p-value = 2.7 × 10-8). At the highest quartile of PRS, the 30-year CRC risk was statistically significantly lower for women taking any MHT than for women not taking any MHT, 3.7% (3.3%-4.0%) vs 6.1% (5.7%-6.5%) (difference 2.4%, P-value = 1.83 × 10-14); these differences were also statistically significant but smaller in magnitude in the lowest PRS quartile, 1.6% (1.4%-1.8%) vs 2.2% (1.9%-2.4%) (difference 0.6%, P-value = 1.01 × 10-3), indicating 4 times greater reduction in absolute risk associated with any MHT use in the highest compared to the lowest quartile of genetic CRC risk. CONCLUSIONS: MHT use has a greater impact on the reduction of CRC risk for women at higher genetic risk. These findings have implications for the development of risk prediction models for CRC and potentially for the consideration of genetic information in the risk-benefit assessment of MHT use.
Published: 2024

2. Florbetapir F 18 amyloid PET and 36-month cognitive decline:a prospective multicenter study

Author: Doraiswamy, PM, Sperling, RA, Johnson, K, Reiman, EM, Wong, TZ, Sabbagh, MN, Sadowsky, CH, Fleisher, AS, Carpenter, A, Joshi, AD, Lu, M, Grundman, M, Mintun, MA, Skovronsky, DM, and Pontecorvo, MJ
Subjects: Alzheimer's Disease, Clinical Trials and Supportive Activities, Clinical Research, Dementia, Neurodegenerative, Aging, Acquired Cognitive Impairment, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Neurological, Aged, Alzheimer Disease, Amyloid beta-Peptides, Aniline Compounds, Brain, Cognitive Dysfunction, Disease Progression, Ethylene Glycols, Female, Follow-Up Studies, Humans, Longitudinal Studies, Male, Neuropsychological Tests, Nootropic Agents, Positron-Emission Tomography, Prospective Studies, Radiopharmaceuticals, alzheimer's disease, amyloid, cognitive decline, florbetapir, MCI, PET, AV45-A11 Study Group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract: This study was designed to evaluate whether subjects with amyloid beta (Aβ) pathology, detected using florbetapir positron emission tomorgraphy (PET), demonstrated greater cognitive decline than subjects without Aβ pathology. Sixty-nine cognitively normal (CN) controls, 52 with recently diagnosed mild cognitive impairment (MCI) and 31 with probable Alzheimer's disease (AD) dementia were included in the study. PET images obtained in these subjects were visually rated as positive (Aβ+) or negative (Aβ-), blind to diagnosis. Fourteen percent (10/69) of CN, 37% (19/52) of MCI and 68% (21/31) of AD were Aβ+. The primary outcome was change in ADAS-Cog score in MCI subjects after 36 months; however, additional outcomes included change on measures of cognition, function and diagnostic status. Aβ+ MCI subjects demonstrated greater worsening compared with Aβ- subjects on the ADAS-Cog over 36 months (5.66 ± 1.47 vs -0.71 ± 1.09, P = 0.0014) as well as on the mini-mental state exam (MMSE), digit symbol substitution (DSS) test, and a verbal fluency test (P < 0.05). Similar to MCI subjects, Aβ+ CN subjects showed greater decline on the ADAS-Cog, digit-symbol-substitution test and verbal fluency (P
Published: 2014

3. Genome-wide interaction analysis of folate for colorectal cancer risk

Author: Bouras, E, Kim, AE, Lin, Y, Morrison, J, Du, M, Albanes, D, Barry, EL, Baurley, JW, Berndt, SI, Bien, SA, Bishop, TD, Brenner, H, Budiarto, A, Burnett-Hartman, A, Campbell, PT, Carreras-Torres, R, Casey, G, Cenggoro, TW, Chan, AT, Chang-Claude, J, Conti, DV, Cotterchio, M, Devall, M, Diez-Obrero, V, Dimou, N, Drew, DA, Figueiredo, JC, Giles, GG, Gruber, SB, Gunter, MJ, Harrison, TA, Hidaka, A, Hoffmeister, M, Huyghe, JR, Joshi, AD, Kawaguchi, ES, Keku, TO, Kundaje, A, Le Marchand, L, Lewinger, JP, Li, L, Lynch, BM, Mahesworo, B, Mannisto, S, Moreno, V, Murphy, N, Newcomb, PA, Obon-Santacana, M, Ose, J, Palmer, JR, Papadimitriou, N, Pardamean, B, Pellatt, AJ, Peoples, AR, Platz, EA, Potter, JD, Qi, L, Qu, C, Rennert, G, Ruiz-Narvaez, E, Sakoda, LC, Schmit, SL, Shcherbina, A, Stern, MC, Su, Y-R, Tangen, CM, Thomas, DC, Tian, Y, Um, CY, van Duijnhoven, FJB, Van Guelpen, B, Visvanathan, K, Wang, J, White, E, Wolk, A, Woods, MO, Ulrich, CM, Hsu, L, Gauderman, WJ, Peters, U, Tsilidis, KK, Bouras, E, Kim, AE, Lin, Y, Morrison, J, Du, M, Albanes, D, Barry, EL, Baurley, JW, Berndt, SI, Bien, SA, Bishop, TD, Brenner, H, Budiarto, A, Burnett-Hartman, A, Campbell, PT, Carreras-Torres, R, Casey, G, Cenggoro, TW, Chan, AT, Chang-Claude, J, Conti, DV, Cotterchio, M, Devall, M, Diez-Obrero, V, Dimou, N, Drew, DA, Figueiredo, JC, Giles, GG, Gruber, SB, Gunter, MJ, Harrison, TA, Hidaka, A, Hoffmeister, M, Huyghe, JR, Joshi, AD, Kawaguchi, ES, Keku, TO, Kundaje, A, Le Marchand, L, Lewinger, JP, Li, L, Lynch, BM, Mahesworo, B, Mannisto, S, Moreno, V, Murphy, N, Newcomb, PA, Obon-Santacana, M, Ose, J, Palmer, JR, Papadimitriou, N, Pardamean, B, Pellatt, AJ, Peoples, AR, Platz, EA, Potter, JD, Qi, L, Qu, C, Rennert, G, Ruiz-Narvaez, E, Sakoda, LC, Schmit, SL, Shcherbina, A, Stern, MC, Su, Y-R, Tangen, CM, Thomas, DC, Tian, Y, Um, CY, van Duijnhoven, FJB, Van Guelpen, B, Visvanathan, K, Wang, J, White, E, Wolk, A, Woods, MO, Ulrich, CM, Hsu, L, Gauderman, WJ, Peters, U, and Tsilidis, KK
Abstract: BACKGROUND: Epidemiological and experimental evidence suggests that higher folate intake is associated with decreased colorectal cancer (CRC) risk; however, the mechanisms underlying this relationship are not fully understood. Genetic variation that may have a direct or indirect impact on folate metabolism can provide insights into folate's role in CRC. OBJECTIVES: Our aim was to perform a genome-wide interaction analysis to identify genetic variants that may modify the association of folate on CRC risk. METHODS: We applied traditional case-control logistic regression, joint 3-degree of freedom, and a 2-step weighted hypothesis approach to test the interactions of common variants (allele frequency >1%) across the genome and dietary folate, folic acid supplement use, and total folate in relation to risk of CRC in 30,550 cases and 42,336 controls from 51 studies from 3 genetic consortia (CCFR, CORECT, GECCO). RESULTS: Inverse associations of dietary, total folate, and folic acid supplement with CRC were found (odds ratio [OR]: 0.93; 95% confidence interval [CI]: 0.90, 0.96; and 0.91; 95% CI: 0.89, 0.94 per quartile higher intake, and 0.82 (95% CI: 0.78, 0.88) for users compared with nonusers, respectively). Interactions (P-interaction < 5×10-8) of folic acid supplement and variants in the 3p25.2 locus (in the region of Synapsin II [SYN2]/tissue inhibitor of metalloproteinase 4 [TIMP4]) were found using traditional interaction analysis, with variant rs150924902 (located upstream to SYN2) showing the strongest interaction. In stratified analyses by rs150924902 genotypes, folate supplementation was associated with decreased CRC risk among those carrying the TT genotype (OR: 0.82; 95% CI: 0.79, 0.86) but increased CRC risk among those carrying the TA genotype (OR: 1.63; 95% CI: 1.29, 2.05), suggesting a qualitative interaction (P-interaction = 1.4×10-8). No interactions were observed for dietary and total folate. CONCLUSIONS: Variation in 3p25.2 locus may modify the assoc
Published: 2023

4. Dynamic Torque Limitation vs Static Torque Limitation for Bone Screws in Pig Bone

Author: Wilkie Jack, Richard Jordan, Joshi Aditya, McFarlane Zoe, Staiger Mark, Rauter Georg, and Möller Knut
Subjects: bone screw, smart screwdriver, parameter identification, automatic, pig bone, Medicine
Abstract: Correctly torquing bone screws is important to achieve good patient outcomes. An automated system has been previously proposed that may allow more objective torquing of bone screws. Here the system is tested vs. a static torque limit in pig bone. 5 screws were first inserted until stripping to calibrate the dynamic and static limits. Then 6 were inserted limited to 80% of the mean stripping torque. Then 7 were inserted using 80% of the dynamic model-predicted stripping torque. The pull-out strength of the dynamic and static insertions were compared and no statistically significant difference was found. Future work should consider at using larger screws and different bone samples, with more repetitions to try and obtain a statistically significant result.
Published: 2024
Full Text: View/download PDF

5. Genome-Wide Interaction Analysis of Genetic Variants With Menopausal Hormone Therapy for Colorectal Cancer Risk

Author: Tian, Y, Kim, AE, Bien, SA, Lin, Y, Qu, C, Harrison, TA, Carreras-Torres, R, Diez-Obrero, V, Dimou, N, Drew, DA, Hidaka, A, Huyghe, JR, Jordahl, KM, Morrison, J, Murphy, N, Obon-Santacana, M, Ulrich, CM, Ose, J, Peoples, AR, Ruiz-Narvaez, EA, Shcherbina, A, Stern, MC, Su, Y-R, van Duijnhoven, FJB, Arndt, V, Baurley, JW, Berndt, S, Bishop, DT, Brenner, H, Buchanan, DD, Chan, AT, Figueiredo, JC, Gallinger, S, Gruber, SB, Harlid, S, Hoffmeister, M, Jenkins, MA, Joshi, AD, Keku, TO, Larsson, SC, Le Marchand, L, Li, L, Giles, GG, Milne, RL, Nan, H, Nassir, R, Ogino, S, Budiarto, A, Platz, EA, Potter, JD, Prentice, RL, Rennert, G, Sakoda, LC, Schoen, RE, Slattery, ML, Thibodeau, SN, Van Guelpen, B, Visvanathan, K, White, E, Wolk, A, Woods, MO, Wu, AH, Campbell, PT, Casey, G, Conti, D, Gunter, MJ, Kundaje, A, Lewinger, JP, Moreno, V, Newcomb, PA, Pardamean, B, Thomas, DC, Tsilidis, KK, Peters, U, Gauderman, WJ, Hsu, L, Chang-Claude, J, Tian, Y, Kim, AE, Bien, SA, Lin, Y, Qu, C, Harrison, TA, Carreras-Torres, R, Diez-Obrero, V, Dimou, N, Drew, DA, Hidaka, A, Huyghe, JR, Jordahl, KM, Morrison, J, Murphy, N, Obon-Santacana, M, Ulrich, CM, Ose, J, Peoples, AR, Ruiz-Narvaez, EA, Shcherbina, A, Stern, MC, Su, Y-R, van Duijnhoven, FJB, Arndt, V, Baurley, JW, Berndt, S, Bishop, DT, Brenner, H, Buchanan, DD, Chan, AT, Figueiredo, JC, Gallinger, S, Gruber, SB, Harlid, S, Hoffmeister, M, Jenkins, MA, Joshi, AD, Keku, TO, Larsson, SC, Le Marchand, L, Li, L, Giles, GG, Milne, RL, Nan, H, Nassir, R, Ogino, S, Budiarto, A, Platz, EA, Potter, JD, Prentice, RL, Rennert, G, Sakoda, LC, Schoen, RE, Slattery, ML, Thibodeau, SN, Van Guelpen, B, Visvanathan, K, White, E, Wolk, A, Woods, MO, Wu, AH, Campbell, PT, Casey, G, Conti, D, Gunter, MJ, Kundaje, A, Lewinger, JP, Moreno, V, Newcomb, PA, Pardamean, B, Thomas, DC, Tsilidis, KK, Peters, U, Gauderman, WJ, Hsu, L, and Chang-Claude, J
Abstract: BACKGROUND: The use of menopausal hormone therapy (MHT) may interact with genetic variants to influence colorectal cancer (CRC) risk. METHODS: We conducted a genome-wide, gene-environment interaction between single nucleotide polymorphisms and the use of any MHT, estrogen only, and combined estrogen-progestogen therapy with CRC risk, among 28 486 postmenopausal women (11 519 CRC patients and 16 967 participants without CRC) from 38 studies, using logistic regression, 2-step method, and 2- or 3-degree-of-freedom joint test. A set-based score test was applied for rare genetic variants. RESULTS: The use of any MHT, estrogen only and estrogen-progestogen were associated with a reduced CRC risk (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.64 to 0.78; OR = 0.65, 95% CI = 0.53 to 0.79; and OR = 0.73, 95% CI = 0.59 to 0.90, respectively). The 2-step method identified a statistically significant interaction between a GRIN2B variant rs117868593 and MHT use, whereby MHT-associated CRC risk was statistically significantly reduced in women with the GG genotype (OR = 0.68, 95% CI = 0.64 to 0.72) but not within strata of GC or CC genotypes. A statistically significant interaction between a DCBLD1 intronic variant at 6q22.1 (rs10782186) and MHT use was identified by the 2-degree-of-freedom joint test. The MHT-associated CRC risk was reduced with increasing number of rs10782186-C alleles, showing odds ratios of 0.78 (95% CI = 0.70 to 0.87) for TT, 0.68 (95% CI = 0.63 to 0.73) for TC, and 0.66 (95% CI = 0.60 to 0.74) for CC genotypes. In addition, 5 genes in rare variant analysis showed suggestive interactions with MHT (2-sided P < 1.2 × 10-4). CONCLUSION: Genetic variants that modify the association between MHT and CRC risk were identified, offering new insights into pathways of CRC carcinogenesis and potential mechanisms involved.
Published: 2022

6. Genetically Predicted Circulating C-Reactive Protein Concentration and Colorectal Cancer Survival: A Mendelian Randomization Consortium Study

Author: Hua, X, Dai, JY, Lindstrom, S, Harrison, TA, Lin, Y, Alberts, SR, Alwers, E, Berndt, S, Brenner, H, Buchanan, DD, Campbell, PT, Casey, G, Chang-Claude, J, Gallinger, S, Giles, GG, Goldberg, RM, Gunter, MJ, Hoffmeister, M, Jenkins, MA, Joshi, AD, Ma, W, Milne, RL, Murphy, N, Pai, RK, Sakoda, LC, Schoen, RE, Shi, Q, Slattery, ML, Song, M, White, E, Le Marchand, L, Chan, AT, Peters, U, Newcomb, PA, Hua, X, Dai, JY, Lindstrom, S, Harrison, TA, Lin, Y, Alberts, SR, Alwers, E, Berndt, S, Brenner, H, Buchanan, DD, Campbell, PT, Casey, G, Chang-Claude, J, Gallinger, S, Giles, GG, Goldberg, RM, Gunter, MJ, Hoffmeister, M, Jenkins, MA, Joshi, AD, Ma, W, Milne, RL, Murphy, N, Pai, RK, Sakoda, LC, Schoen, RE, Shi, Q, Slattery, ML, Song, M, White, E, Le Marchand, L, Chan, AT, Peters, U, and Newcomb, PA
Abstract: BACKGROUND: A positive association between circulating C-reactive protein (CRP) and colorectal cancer survival was reported in observational studies, which are susceptible to unmeasured confounding and reverse causality. We used a Mendelian randomization approach to evaluate the association between genetically predicted CRP concentrations and colorectal cancer-specific survival. METHODS: We used individual-level data for 16,918 eligible colorectal cancer cases of European ancestry from 15 studies within the International Survival Analysis of Colorectal Cancer Consortium. We calculated a genetic-risk score based on 52 CRP-associated genetic variants identified from genome-wide association studies. Because of the non-collapsibility of hazard ratios from Cox proportional hazards models, we used the additive hazards model to calculate hazard differences (HD) and 95% confidence intervals (CI) for the association between genetically predicted CRP concentrations and colorectal cancer-specific survival, overall and by stage at diagnosis and tumor location. Analyses were adjusted for age at diagnosis, sex, body mass index, genotyping platform, study, and principal components. RESULTS: Of the 5,395 (32%) deaths accrued over up to 10 years of follow-up, 3,808 (23%) were due to colorectal cancer. Genetically predicted CRP concentration was not associated with colorectal cancer-specific survival (HD, -1.15; 95% CI, -2.76 to 0.47 per 100,000 person-years; P = 0.16). Similarly, no associations were observed in subgroup analyses by stage at diagnosis or tumor location. CONCLUSIONS: Despite adequate power to detect moderate associations, our results did not support a causal effect of circulating CRP concentrations on colorectal cancer-specific survival. IMPACT: Future research evaluating genetically determined levels of other circulating inflammatory biomarkers (i.e., IL6) with colorectal cancer survival outcomes is needed.
Published: 2021

7. A Polygenic Risk Score Predicts Incident Prostate Cancer Risk in Older Men but Does Not Select for Clinically Significant Disease.

Author: Bakshi, A, Riaz, M, Orchard, SG, Carr, PR, Joshi, AD, Cao, Y, Rebello, R, Nguyen-Dumont, T, Southey, MC, Millar, JL, Gately, L, Gibbs, P, Ford, LG, Parnes, HL, Chan, AT, McNeil, JJ, Lacaze, P, Bakshi, A, Riaz, M, Orchard, SG, Carr, PR, Joshi, AD, Cao, Y, Rebello, R, Nguyen-Dumont, T, Southey, MC, Millar, JL, Gately, L, Gibbs, P, Ford, LG, Parnes, HL, Chan, AT, McNeil, JJ, and Lacaze, P
Abstract: Despite the high prevalence of prostate cancer in older men, the predictive value of a polygenic risk score (PRS) remains uncertain in men aged ≥70 years. We used a 6.6 million-variant PRS to predict the risk of incident prostate cancer in a prospective study of 5701 men of European descent aged ≥70 years (mean age 75 years) enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) clinical trial. The study endpoint was prostate cancer, including metastatic or non-metastatic disease, confirmed by an expert panel. After excluding participants with a history of prostate cancer at enrolment, we used a multivariable Cox proportional hazards model to assess the association between the PRS and incident prostate cancer risk, adjusting for covariates. Additionally, we examined the distribution of Gleason grade groups by PRS group to determine if a higher PRS was associated with higher grade disease. We tested for interaction between the PRS and aspirin treatment. Logistic regression was used to independently assess the association of the PRS with prevalent (pre-trial) prostate cancer, reported in medical histories. During a median follow-up time of 4.6 years, 218 of the 5701 participants (3.8%) were diagnosed with prostate cancer. The PRS predicted incident risk with a hazard ratio (HR) of 1.52 per standard deviation (SD) (95% confidence interval (CI) 1.33-1.74, p < 0.001). Men in the top quintile of the PRS distribution had an almost three times higher risk of prostate cancer than men in the lowest quintile (HR = 2.99 (95% CI 1.90-4.27), p < 0.001). However, a higher PRS was not associated with a higher Gleason grade groups. We found no interaction between aspirin treatment and the PRS for prostate cancer risk. The PRS was also associated with prevalent prostate cancer (odds ratio = 1.80 per SD (95% CI 1.65-1.96), p < 0.001).While a PRS for prostate cancer is strongly associated with incident risk in men aged ≥70 years, the clinical utility of the PRS as a biomark
Published: 2021

8. Genetic architectures of proximal and distal colorectal cancer are partly distinct

Author: Huyghe, JR, Harrison, TA, Bien, SA, Hampel, H, Figueiredo, JC, Schmit, SL, Conti, D, Chen, S, Qu, C, Lin, Y, Barfield, R, Baron, JA, Cross, AJ, Diergaarde, B, Duggan, D, Harlid, S, Imaz, L, Kang, HM, Levine, DM, Perduca, V, Perez-Cornago, A, Sakoda, LC, Schumacher, FR, Slattery, ML, Toland, AE, van Duijnhoven, FJB, Van Guelpen, B, Agudo, A, Albanes, D, Alonso, MH, Anderson, K, Arnau-Collell, C, Arndt, V, Banbury, BL, Bassik, MC, Berndt, S, Bezieau, S, Bishop, DT, Boehm, J, Boeing, H, Boutron-Ruault, M-C, Brenner, H, Brezina, S, Buch, S, Buchanan, DD, Burnett-Hartman, A, Caan, BJ, Campbell, PT, Carr, PR, Castells, A, Castellvi-Bel, S, Chan, AT, Chang-Claude, J, Chanock, SJ, Curtis, KR, de la Chapelle, A, Easton, DF, English, DR, Feskens, EJM, Gala, M, Gallinger, SJ, Gauderman, WJ, Giles, GG, Goodman, PJ, Grady, WM, Grove, JS, Gsur, A, Gunter, MJ, Haile, RW, Hampe, J, Hoffmeister, M, Hopper, JL, Hsu, W-L, Huang, W-Y, Hudson, TJ, Jenab, M, Jenkins, MA, Joshi, AD, Keku, TO, Kooperberg, C, Kuhn, T, Kury, S, Le Marchand, L, Lejbkowicz, F, Li, C, Li, L, Lieb, W, Lindblom, A, Lindor, NM, Mannisto, S, Markowitz, SD, Milne, RL, Moreno, L, Murphy, N, Nassir, R, Offit, K, Ogino, S, Panico, S, Parfrey, PS, Pearlman, R, Pharoah, PDP, Phipps, A, Platz, EA, Potter, JD, Prentice, RL, Qi, L, Raskin, L, Rennert, G, Rennert, HS, Riboli, E, Schafmayer, C, Schoen, RE, Seminara, D, Song, M, Su, Y-R, Tangen, CM, Thibodeau, SN, Thomas, DC, Trichopoulou, A, Ulrich, CM, Visvanathan, K, Vodicka, P, Vodickova, L, Vymetalkova, V, Weigl, K, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Wu, AH, Abecasis, GR, Nickerson, DA, Scacheri, PC, Kundaje, A, Casey, G, Gruber, SB, Hsu, L, Moreno, V, Hayes, RB, Newcomb, PA, Peters, U, Huyghe, JR, Harrison, TA, Bien, SA, Hampel, H, Figueiredo, JC, Schmit, SL, Conti, D, Chen, S, Qu, C, Lin, Y, Barfield, R, Baron, JA, Cross, AJ, Diergaarde, B, Duggan, D, Harlid, S, Imaz, L, Kang, HM, Levine, DM, Perduca, V, Perez-Cornago, A, Sakoda, LC, Schumacher, FR, Slattery, ML, Toland, AE, van Duijnhoven, FJB, Van Guelpen, B, Agudo, A, Albanes, D, Alonso, MH, Anderson, K, Arnau-Collell, C, Arndt, V, Banbury, BL, Bassik, MC, Berndt, S, Bezieau, S, Bishop, DT, Boehm, J, Boeing, H, Boutron-Ruault, M-C, Brenner, H, Brezina, S, Buch, S, Buchanan, DD, Burnett-Hartman, A, Caan, BJ, Campbell, PT, Carr, PR, Castells, A, Castellvi-Bel, S, Chan, AT, Chang-Claude, J, Chanock, SJ, Curtis, KR, de la Chapelle, A, Easton, DF, English, DR, Feskens, EJM, Gala, M, Gallinger, SJ, Gauderman, WJ, Giles, GG, Goodman, PJ, Grady, WM, Grove, JS, Gsur, A, Gunter, MJ, Haile, RW, Hampe, J, Hoffmeister, M, Hopper, JL, Hsu, W-L, Huang, W-Y, Hudson, TJ, Jenab, M, Jenkins, MA, Joshi, AD, Keku, TO, Kooperberg, C, Kuhn, T, Kury, S, Le Marchand, L, Lejbkowicz, F, Li, C, Li, L, Lieb, W, Lindblom, A, Lindor, NM, Mannisto, S, Markowitz, SD, Milne, RL, Moreno, L, Murphy, N, Nassir, R, Offit, K, Ogino, S, Panico, S, Parfrey, PS, Pearlman, R, Pharoah, PDP, Phipps, A, Platz, EA, Potter, JD, Prentice, RL, Qi, L, Raskin, L, Rennert, G, Rennert, HS, Riboli, E, Schafmayer, C, Schoen, RE, Seminara, D, Song, M, Su, Y-R, Tangen, CM, Thibodeau, SN, Thomas, DC, Trichopoulou, A, Ulrich, CM, Visvanathan, K, Vodicka, P, Vodickova, L, Vymetalkova, V, Weigl, K, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Wu, AH, Abecasis, GR, Nickerson, DA, Scacheri, PC, Kundaje, A, Casey, G, Gruber, SB, Hsu, L, Moreno, V, Hayes, RB, Newcomb, PA, and Peters, U
Abstract: OBJECTIVE: An understanding of the etiologic heterogeneity of colorectal cancer (CRC) is critical for improving precision prevention, including individualized screening recommendations and the discovery of novel drug targets and repurposable drug candidates for chemoprevention. Known differences in molecular characteristics and environmental risk factors among tumors arising in different locations of the colorectum suggest partly distinct mechanisms of carcinogenesis. The extent to which the contribution of inherited genetic risk factors for CRC differs by anatomical subsite of the primary tumor has not been examined. DESIGN: To identify new anatomical subsite-specific risk loci, we performed genome-wide association study (GWAS) meta-analyses including data of 48 214 CRC cases and 64 159 controls of European ancestry. We characterised effect heterogeneity at CRC risk loci using multinomial modelling. RESULTS: We identified 13 loci that reached genome-wide significance (p<5×10-8) and that were not reported by previous GWASs for overall CRC risk. Multiple lines of evidence support candidate genes at several of these loci. We detected substantial heterogeneity between anatomical subsites. Just over half (61) of 109 known and new risk variants showed no evidence for heterogeneity. In contrast, 22 variants showed association with distal CRC (including rectal cancer), but no evidence for association or an attenuated association with proximal CRC. For two loci, there was strong evidence for effects confined to proximal colon cancer. CONCLUSION: Genetic architectures of proximal and distal CRC are partly distinct. Studies of risk factors and mechanisms of carcinogenesis, and precision prevention strategies should take into consideration the anatomical subsite of the tumour.
Published: 2021

9. Genomic Risk Prediction for Breast Cancer in Older Women

Author: Lacaze, P, Bakshi, A, Riaz, M, Orchard, SG, Tiller, J, Neumann, JT, Carr, PR, Joshi, AD, Cao, Y, Warner, ET, Manning, A, Nguyen-Dumont, T, Southey, MC, Milne, RL, Ford, L, Sebra, R, Schadt, E, Gately, L, Gibbs, P, Thompson, BA, Macrae, FA, James, P, Winship, I, McLean, C, Zalcberg, JR, Woods, RL, Chan, AT, Murray, AM, McNeil, JJ, Lacaze, P, Bakshi, A, Riaz, M, Orchard, SG, Tiller, J, Neumann, JT, Carr, PR, Joshi, AD, Cao, Y, Warner, ET, Manning, A, Nguyen-Dumont, T, Southey, MC, Milne, RL, Ford, L, Sebra, R, Schadt, E, Gately, L, Gibbs, P, Thompson, BA, Macrae, FA, James, P, Winship, I, McLean, C, Zalcberg, JR, Woods, RL, Chan, AT, Murray, AM, and McNeil, JJ
Abstract: Genomic risk prediction models for breast cancer (BC) have been predominantly developed with data from women aged 40-69 years. Prospective studies of older women aged ≥70 years have been limited. We assessed the effect of a 313-variant polygenic risk score (PRS) for BC in 6339 older women aged ≥70 years (mean age 75 years) enrolled into the ASPREE trial, a randomized double-blind placebo-controlled clinical trial investigating the effect of daily 100 mg aspirin on disability-free survival. We evaluated incident BC diagnoses over a median follow-up time of 4.7 years. A multivariable Cox regression model including conventional BC risk factors was applied to prospective data, and re-evaluated after adding the PRS. We also assessed the association of rare pathogenic variants (PVs) in BC susceptibility genes (BRCA1/BRCA2/PALB2/CHEK2/ATM). The PRS, as a continuous variable, was an independent predictor of incident BC (hazard ratio (HR) per standard deviation (SD) = 1.4, 95% confidence interval (CI) 1.3-1.6) and hormone receptor (ER/PR)-positive disease (HR = 1.5 (CI 1.2-1.9)). Women in the top quintile of the PRS distribution had over two-fold higher risk of BC than women in the lowest quintile (HR = 2.2 (CI 1.2-3.9)). The concordance index of the model without the PRS was 0.62 (95% CI 0.56-0.68), which improved after addition of the PRS to 0.65 (95% CI 0.59-0.71). Among 41 (0.6%) carriers of PVs in BC susceptibility genes, we observed no incident BC diagnoses. Our study demonstrates that a PRS predicts incident BC risk in women aged 70 years and older, suggesting potential clinical utility extends to this older age group.
Published: 2021

10. Cumulative Burden of Colorectal Cancer Associated Genetic Variants Is More Strongly Associated With Early-Onset vs Late-Onset Cancer

Author: Archambault, AN, Su, Y-R, Jeon, J, Thomas, M, Lin, Y, Conti, DV, Win, AK, Sakoda, LC, Lansdorp-Vogelaar, I, Peterse, EFP, Zauber, AG, Duggan, D, Holowatyj, AN, Huyghe, JR, Brenner, H, Cotterchio, M, Bezieau, S, Schmit, SL, Edlund, CK, Southey, MC, MacInnis, RJ, Campbell, PT, Chang-Claude, J, Slattery, ML, Chan, AT, Joshi, AD, Song, M, Cao, Y, Woods, MO, White, E, Weinstein, SJ, Ulrich, CM, Hoffmeister, M, Bien, SA, Harrison, TA, Hampe, J, Li, CI, Schafmayer, C, Offit, K, Pharoah, PD, Moreno, V, Lindblom, A, Wolk, A, Wu, AH, Li, L, Gunter, MJ, Gsur, A, Keku, TO, Pearlman, R, Bishop, DT, Castellvi-Bel, S, Moreira, L, Vodicka, P, Kampman, E, Giles, GG, Albanes, D, Baron, JA, Berndt, SI, Brezina, S, Buch, S, Buchanan, DD, Trichopoulou, A, Severi, G, Chirlaque, M-D, Sanchez, M-J, Palli, D, Kuhn, T, Murphy, N, Cross, AJ, Burnett-Hartman, AN, Chanock, SJ, de la Chapelle, A, Easton, DF, Elliott, F, English, DR, Feskens, EJM, FitzGerald, LM, Goodman, PJ, Hopper, JL, Hudson, TJ, Hunter, DJ, Jacobs, EJ, Joshu, CE, Kury, S, Markowitz, SD, Milne, RL, Platz, EA, Rennert, G, Rennert, HS, Schumacher, FR, Sandler, RS, Seminara, D, Tangen, CM, Thibodeau, SN, Toland, AE, van Duijnhoven, FJB, Visvanathan, K, Vodickova, L, Potter, JD, Mannisto, S, Weigl, K, Figueiredo, J, Martin, V, Larsson, SC, Parfrey, PS, Huang, W-Y, Lenz, H-J, Castelao, JE, Gago-Dominguez, M, Munoz-Garzon, V, Mancao, C, Haiman, CA, Wilkens, LR, Siegel, E, Barry, E, Younghusband, B, Van Guelpen, B, Harlid, S, Zeleniuch-Jacquotte, A, Liang, PS, Du, M, Casey, G, Lindor, NM, Le Marchand, L, Gallinger, SJ, Jenkins, MA, Newcomb, PA, Gruber, SB, Schoen, RE, Hampel, H, Corley, DA, Hsu, L, Peters, U, Hayes, RB, Archambault, AN, Su, Y-R, Jeon, J, Thomas, M, Lin, Y, Conti, DV, Win, AK, Sakoda, LC, Lansdorp-Vogelaar, I, Peterse, EFP, Zauber, AG, Duggan, D, Holowatyj, AN, Huyghe, JR, Brenner, H, Cotterchio, M, Bezieau, S, Schmit, SL, Edlund, CK, Southey, MC, MacInnis, RJ, Campbell, PT, Chang-Claude, J, Slattery, ML, Chan, AT, Joshi, AD, Song, M, Cao, Y, Woods, MO, White, E, Weinstein, SJ, Ulrich, CM, Hoffmeister, M, Bien, SA, Harrison, TA, Hampe, J, Li, CI, Schafmayer, C, Offit, K, Pharoah, PD, Moreno, V, Lindblom, A, Wolk, A, Wu, AH, Li, L, Gunter, MJ, Gsur, A, Keku, TO, Pearlman, R, Bishop, DT, Castellvi-Bel, S, Moreira, L, Vodicka, P, Kampman, E, Giles, GG, Albanes, D, Baron, JA, Berndt, SI, Brezina, S, Buch, S, Buchanan, DD, Trichopoulou, A, Severi, G, Chirlaque, M-D, Sanchez, M-J, Palli, D, Kuhn, T, Murphy, N, Cross, AJ, Burnett-Hartman, AN, Chanock, SJ, de la Chapelle, A, Easton, DF, Elliott, F, English, DR, Feskens, EJM, FitzGerald, LM, Goodman, PJ, Hopper, JL, Hudson, TJ, Hunter, DJ, Jacobs, EJ, Joshu, CE, Kury, S, Markowitz, SD, Milne, RL, Platz, EA, Rennert, G, Rennert, HS, Schumacher, FR, Sandler, RS, Seminara, D, Tangen, CM, Thibodeau, SN, Toland, AE, van Duijnhoven, FJB, Visvanathan, K, Vodickova, L, Potter, JD, Mannisto, S, Weigl, K, Figueiredo, J, Martin, V, Larsson, SC, Parfrey, PS, Huang, W-Y, Lenz, H-J, Castelao, JE, Gago-Dominguez, M, Munoz-Garzon, V, Mancao, C, Haiman, CA, Wilkens, LR, Siegel, E, Barry, E, Younghusband, B, Van Guelpen, B, Harlid, S, Zeleniuch-Jacquotte, A, Liang, PS, Du, M, Casey, G, Lindor, NM, Le Marchand, L, Gallinger, SJ, Jenkins, MA, Newcomb, PA, Gruber, SB, Schoen, RE, Hampel, H, Corley, DA, Hsu, L, Peters, U, and Hayes, RB
Abstract: BACKGROUND & AIMS: Early-onset colorectal cancer (CRC, in persons younger than 50 years old) is increasing in incidence; yet, in the absence of a family history of CRC, this population lacks harmonized recommendations for prevention. We aimed to determine whether a polygenic risk score (PRS) developed from 95 CRC-associated common genetic risk variants was associated with risk for early-onset CRC. METHODS: We studied risk for CRC associated with a weighted PRS in 12,197 participants younger than 50 years old vs 95,865 participants 50 years or older. PRS was calculated based on single nucleotide polymorphisms associated with CRC in a large-scale genome-wide association study as of January 2019. Participants were pooled from 3 large consortia that provided clinical and genotyping data: the Colon Cancer Family Registry, the Colorectal Transdisciplinary Study, and the Genetics and Epidemiology of Colorectal Cancer Consortium and were all of genetically defined European descent. Findings were replicated in an independent cohort of 72,573 participants. RESULTS: Overall associations with CRC per standard deviation of PRS were significant for early-onset cancer, and were stronger compared with late-onset cancer (P for interaction = .01); when we compared the highest PRS quartile with the lowest, risk increased 3.7-fold for early-onset CRC (95% CI 3.28-4.24) vs 2.9-fold for late-onset CRC (95% CI 2.80-3.04). This association was strongest for participants without a first-degree family history of CRC (P for interaction = 5.61 × 10-5). When we compared the highest with the lowest quartiles in this group, risk increased 4.3-fold for early-onset CRC (95% CI 3.61-5.01) vs 2.9-fold for late-onset CRC (95% CI 2.70-3.00). Sensitivity analyses were consistent with these findings. CONCLUSIONS: In an analysis of associations with CRC per standard deviation of PRS, we found the cumulative burden of CRC-associated common genetic variants to associate with early-onset cancer, and to be mo
Published: 2020

11. Functional informed genome-wide interaction analysis of body mass index, diabetes and colorectal cancer risk

Author: Xia, Z, Su, Y-R, Petersen, P, Qi, L, Kim, AE, Figueiredo, JC, Lin, Y, Nan, H, Sakoda, LC, Albanes, D, Berndt, SI, Bezieau, S, Bien, S, Buchanan, DD, Casey, G, Chan, AT, Conti, DV, Drew, DA, Gallinger, SJ, Gauderman, WJ, Giles, GG, Gruber, SB, Gunter, MJ, Hoffmeister, M, Jenkins, MA, Joshi, AD, Le Marchand, L, Lewinger, JP, Li, L, Lindor, NM, Moreno, V, Murphy, N, Nassir, R, Newcomb, PA, Ogino, S, Rennert, G, Song, M, Wang, X, Wolk, A, Woods, MO, Brenner, H, White, E, Slattery, ML, Giovannucci, EL, Chang-Claude, J, Pharoah, PDP, Hsu, L, Campbell, PT, Peters, U, Xia, Z, Su, Y-R, Petersen, P, Qi, L, Kim, AE, Figueiredo, JC, Lin, Y, Nan, H, Sakoda, LC, Albanes, D, Berndt, SI, Bezieau, S, Bien, S, Buchanan, DD, Casey, G, Chan, AT, Conti, DV, Drew, DA, Gallinger, SJ, Gauderman, WJ, Giles, GG, Gruber, SB, Gunter, MJ, Hoffmeister, M, Jenkins, MA, Joshi, AD, Le Marchand, L, Lewinger, JP, Li, L, Lindor, NM, Moreno, V, Murphy, N, Nassir, R, Newcomb, PA, Ogino, S, Rennert, G, Song, M, Wang, X, Wolk, A, Woods, MO, Brenner, H, White, E, Slattery, ML, Giovannucci, EL, Chang-Claude, J, Pharoah, PDP, Hsu, L, Campbell, PT, and Peters, U
Abstract: BACKGROUND: Body mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology. METHODS: To improve statistical power and interpretation for gene-environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m2 ) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype-Tissue Expression Project for all genes with heritability ≥1%. We used a mixed-effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI-CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR <0.2. RESULTS: Among 4839 genes tested, genetically predicted expressions of FOXA1 (P = 3.15 × 10-5 ), PSMC5 (P = 4.51 × 10-4 ) and CD33 (P = 2.71 × 10-4 ) modified the association of BMI on CRC risk for men; KIAA0753 (P = 2.29 × 10-5 ) and SCN1B (P = 2.76 × 10-4 ) modified the association of BMI on CRC risk for women; and PTPN2 modified the association between diabetes and CRC risk in both sexes (P = 2.31 × 10-5 ). CONCLUSIONS: Aggregating G × E interactions and incorporating functional information, we discovered novel genes that may interact with BMI and diabetes on CRC risk.
Published: 2020

12. Circulating bilirubin levels and risk of colorectal cancer: serological and Mendelian randomization analyses

Author: Seyed Khoei, N, Jenab, M, Murphy, N, Banbury, BL, Carreras-Torres, R, Viallon, V, Kuehn, T, Bueno-de-Mesquita, B, Aleksandrova, K, Cross, AJ, Weiderpass, E, Stepien, M, Bulmer, A, Tjonneland, A, Boutron-Ruault, M-C, Severi, G, Carbonnel, F, Katzke, V, Boeing, H, Bergmann, MM, Trichopoulou, A, Karakatsani, A, Martimianaki, G, Palli, D, Tagliabue, G, Panico, S, Tumino, R, Sacerdote, C, Skeie, G, Merino, S, Bonet, C, Rodriguez-Barranco, M, Gil, L, Chirlaque, M-D, Ardanaz, E, Myte, R, Hultdin, J, Perez-Cornago, A, Aune, D, Tsilidis, K, Albanes, Baron, JA, Berndt, SI, Bezieau, S, Brenner, H, Campbell, PT, Casey, G, Chan, AT, Chang-Claude, J, Chanock, SJ, Cotterchio, M, Gallinger, S, Gruber, SB, Haile, RW, Hampe, J, Hoffmeister, M, Hopper, JL, Hsu, L, Huyghe, JR, Jenkins, MA, Joshi, AD, Kampman, E, Larsson, SC, Le Marchand, L, Li, CI, Li, L, Lindblom, A, Lindor, NM, Martin, V, Moreno, V, Newcomb, PA, Offit, K, Ogino, S, Parfrey, PS, Pharoah, PDP, Rennert, G, Sakoda, LC, Schafmayer, C, Schmit, SL, Schoen, RE, Slattery, ML, Thibodeau, SN, Ulrich, CM, van Duijnhoven, FJB, Weigl, K, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Wu, AH, Zhang, X, Ferrari, P, Anton, G, Peters, A, Peters, U, Gunter, MJ, Wagner, K-H, Freisling, H, Seyed Khoei, N, Jenab, M, Murphy, N, Banbury, BL, Carreras-Torres, R, Viallon, V, Kuehn, T, Bueno-de-Mesquita, B, Aleksandrova, K, Cross, AJ, Weiderpass, E, Stepien, M, Bulmer, A, Tjonneland, A, Boutron-Ruault, M-C, Severi, G, Carbonnel, F, Katzke, V, Boeing, H, Bergmann, MM, Trichopoulou, A, Karakatsani, A, Martimianaki, G, Palli, D, Tagliabue, G, Panico, S, Tumino, R, Sacerdote, C, Skeie, G, Merino, S, Bonet, C, Rodriguez-Barranco, M, Gil, L, Chirlaque, M-D, Ardanaz, E, Myte, R, Hultdin, J, Perez-Cornago, A, Aune, D, Tsilidis, K, Albanes, Baron, JA, Berndt, SI, Bezieau, S, Brenner, H, Campbell, PT, Casey, G, Chan, AT, Chang-Claude, J, Chanock, SJ, Cotterchio, M, Gallinger, S, Gruber, SB, Haile, RW, Hampe, J, Hoffmeister, M, Hopper, JL, Hsu, L, Huyghe, JR, Jenkins, MA, Joshi, AD, Kampman, E, Larsson, SC, Le Marchand, L, Li, CI, Li, L, Lindblom, A, Lindor, NM, Martin, V, Moreno, V, Newcomb, PA, Offit, K, Ogino, S, Parfrey, PS, Pharoah, PDP, Rennert, G, Sakoda, LC, Schafmayer, C, Schmit, SL, Schoen, RE, Slattery, ML, Thibodeau, SN, Ulrich, CM, van Duijnhoven, FJB, Weigl, K, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Wu, AH, Zhang, X, Ferrari, P, Anton, G, Peters, A, Peters, U, Gunter, MJ, Wagner, K-H, and Freisling, H
Abstract: BACKGROUND: Bilirubin, a byproduct of hemoglobin breakdown and purported anti-oxidant, is thought to be cancer preventive. We conducted complementary serological and Mendelian randomization (MR) analyses to investigate whether alterations in circulating levels of bilirubin are associated with risk of colorectal cancer (CRC). We decided a priori to perform analyses separately in men and women based on suggestive evidence that associations may differ by sex. METHODS: In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition (EPIC), pre-diagnostic unconjugated bilirubin (UCB, the main component of total bilirubin) concentrations were measured by high-performance liquid chromatography in plasma samples of 1386 CRC cases and their individually matched controls. Additionally, 115 single-nucleotide polymorphisms (SNPs) robustly associated (P < 5 × 10-8) with circulating total bilirubin were instrumented in a 2-sample MR to test for a potential causal effect of bilirubin on CRC risk in 52,775 CRC cases and 45,940 matched controls in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), the Colon Cancer Family Registry (CCFR), and the Colorectal Transdisciplinary (CORECT) study. RESULTS: The associations between circulating UCB levels and CRC risk differed by sex (Pheterogeneity = 0.008). Among men, higher levels of UCB were positively associated with CRC risk (odds ratio [OR] = 1.19, 95% confidence interval [CI] = 1.04-1.36; per 1-SD increment of log-UCB). In women, an inverse association was observed (OR = 0.86 (0.76-0.97)). In the MR analysis of the main UGT1A1 SNP (rs6431625), genetically predicted higher levels of total bilirubin were associated with a 7% increase in CRC risk in men (OR = 1.07 (1.02-1.12); P = 0.006; per 1-SD increment of total bilirubin), while there was no association in women (OR = 1.01 (0.96-1.06); P = 0.73). Raised bilirubin levels, predicted by instrumental variables excluding rs6431625, we
Published: 2020

13. Meta-analysis of 16 studies of the association of alcohol with colorectal cancer

Author: McNabb, S, Harrison, TA, Albanes, D, Berndt, SI, Brenner, H, Caan, BJ, Campbell, PT, Cao, Y, Chang-Claude, J, Chan, A, Chen, Z, English, DR, Giles, GG, Giovannucci, EL, Goodman, PJ, Hayes, RB, Hoffmeister, M, Jacobs, EJ, Joshi, AD, Larsson, SC, Le Marchand, L, Li, L, Lin, Y, Mannisto, S, Milne, RL, Nan, H, Newton, CC, Ogino, S, Parfrey, PS, Petersen, PS, Potter, JD, Schoen, RE, Slattery, ML, Su, Y-R, Tangen, CM, Tucker, TC, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Phipps, AI, Peters, U, McNabb, S, Harrison, TA, Albanes, D, Berndt, SI, Brenner, H, Caan, BJ, Campbell, PT, Cao, Y, Chang-Claude, J, Chan, A, Chen, Z, English, DR, Giles, GG, Giovannucci, EL, Goodman, PJ, Hayes, RB, Hoffmeister, M, Jacobs, EJ, Joshi, AD, Larsson, SC, Le Marchand, L, Li, L, Lin, Y, Mannisto, S, Milne, RL, Nan, H, Newton, CC, Ogino, S, Parfrey, PS, Petersen, PS, Potter, JD, Schoen, RE, Slattery, ML, Su, Y-R, Tangen, CM, Tucker, TC, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Phipps, AI, and Peters, U
Abstract: Alcohol consumption is an established risk factor for colorectal cancer (CRC). However, while studies have consistently reported elevated risk of CRC among heavy drinkers, associations at moderate levels of alcohol consumption are less clear. We conducted a combined analysis of 16 studies of CRC to examine the shape of the alcohol-CRC association, investigate potential effect modifiers of the association, and examine differential effects of alcohol consumption by cancer anatomic site and stage. We collected information on alcohol consumption for 14,276 CRC cases and 15,802 controls from 5 case-control and 11 nested case-control studies of CRC. We compared adjusted logistic regression models with linear and restricted cubic splines to select a model that best fit the association between alcohol consumption and CRC. Study-specific results were pooled using fixed-effects meta-analysis. Compared to non-/occasional drinking (≤1 g/day), light/moderate drinking (up to 2 drinks/day) was associated with a decreased risk of CRC (odds ratio [OR]: 0.92, 95% confidence interval [CI]: 0.88-0.98, p = 0.005), heavy drinking (2-3 drinks/day) was not significantly associated with CRC risk (OR: 1.11, 95% CI: 0.99-1.24, p = 0.08) and very heavy drinking (more than 3 drinks/day) was associated with a significant increased risk (OR: 1.25, 95% CI: 1.11-1.40, p < 0.001). We observed no evidence of interactions with lifestyle risk factors or of differences by cancer site or stage. These results provide further evidence that there is a J-shaped association between alcohol consumption and CRC risk. This overall pattern was not significantly modified by other CRC risk factors and there was no effect heterogeneity by tumor site or stage.
Published: 2020

14. Genetic Predictors of Circulating 25-Hydroxyvitamin D and Prognosis after Colorectal Cancer.

Author: Neumeyer, S, Butterbach, K, Banbury, BL, Berndt, SI, Campbell, PT, Chlebowski, RT, Chan, AT, Giovannucci, EL, Joshi, AD, Ogino, S, Song, M, McCullough, ML, Maalmi, H, Manson, JE, Sakoda, LC, Schoen, RE, Slattery, ML, White, E, Win, AK, Figueiredo, JC, Hopper, JL, Macrae, FA, Peters, U, Brenner, H, Hoffmeister, M, Newcomb, PA, Chang-Claude, J, Neumeyer, S, Butterbach, K, Banbury, BL, Berndt, SI, Campbell, PT, Chlebowski, RT, Chan, AT, Giovannucci, EL, Joshi, AD, Ogino, S, Song, M, McCullough, ML, Maalmi, H, Manson, JE, Sakoda, LC, Schoen, RE, Slattery, ML, White, E, Win, AK, Figueiredo, JC, Hopper, JL, Macrae, FA, Peters, U, Brenner, H, Hoffmeister, M, Newcomb, PA, and Chang-Claude, J
Abstract: Background: Low serum 25-hydroxyvitamin D [25(OH)D] concentrations in patients with colorectal cancer have been consistently associated with higher mortality in observational studies. It is unclear whether low 25(OH)D levels directly influence colorectal cancer mortality. To minimize bias, we use genetic variants associated with vitamin D levels to evaluate the association with overall and colorectal cancer–specific survival. Methods: Six genetic variants have been robustly identified to be associated with 25(OH)D levels in genome-wide association studies. On the basis of data from the International Survival Analysis in Colorectal Cancer Consortium, the individual genetic variants and a weighted genetic risk score were tested for association with overall and colorectal cancer–specific survival using Cox proportional hazards models in 7,657 patients with stage I to IV colorectal cancer, of whom 2,438 died from any cause and 1,648 died from colorectal cancer. Results: The 25(OH)D decreasing allele of SNP rs2282679 (GC gene, encodes group-specific component/vitamin D–binding protein) was associated with poorer colorectal cancer–specific survival, although not significant after multiple-testing correction. None of the other five SNPs showed an association. The genetic risk score showed nonsignificant associations with increased overall [HR = 1.54; confidence interval (CI), 0.86–2.78] and colorectal cancer–specific mortality (HR = 1.76; 95% CI, 0.86–3.58). A significant increased risk of overall mortality was observed in women (HR = 3.26; 95% CI, 1.45–7.33; Pheterogeneity = 0.01) and normal-weight individuals (HR = 4.14; 95% CI, 1.50–11.43, Pheterogeneity = 0.02). Conclusions: Our results provided little evidence for an association of genetic predisposition of lower vitamin D levels with increased overall or colorectal cancer–specific survival, although power might have been an issue.
Published: 2020

15. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study.

Author: Nguyen, LH, Drew, DA, Graham, MS, Joshi, AD, Guo, C-G, Ma, W, Mehta, RS, Warner, ET, Sikavi, DR, Lo, C-H, Kwon, S, Song, M, Mucci, LA, Stampfer, MJ, Willett, WC, Eliassen, AH, Hart, JE, Chavarro, JE, Rich-Edwards, JW, Davies, R, Capdevila, J, Lee, KA, Lochlainn, MN, Varsavsky, T, Sudre, CH, Cardoso, MJ, Wolf, J, Spector, TD, Ourselin, S, Steves, CJ, Chan, AT, COronavirus Pandemic Epidemiology Consortium, Nguyen, LH, Drew, DA, Graham, MS, Joshi, AD, Guo, C-G, Ma, W, Mehta, RS, Warner, ET, Sikavi, DR, Lo, C-H, Kwon, S, Song, M, Mucci, LA, Stampfer, MJ, Willett, WC, Eliassen, AH, Hart, JE, Chavarro, JE, Rich-Edwards, JW, Davies, R, Capdevila, J, Lee, KA, Lochlainn, MN, Varsavsky, T, Sudre, CH, Cardoso, MJ, Wolf, J, Spector, TD, Ourselin, S, Steves, CJ, Chan, AT, and COronavirus Pandemic Epidemiology Consortium
Abstract: BACKGROUND: Data for front-line health-care workers and risk of COVID-19 are limited. We sought to assess risk of COVID-19 among front-line health-care workers compared with the general community and the effect of personal protective equipment (PPE) on risk. METHODS: We did a prospective, observational cohort study in the UK and the USA of the general community, including front-line health-care workers, using self-reported data from the COVID Symptom Study smartphone application (app) from March 24 (UK) and March 29 (USA) to April 23, 2020. Participants were voluntary users of the app and at first use provided information on demographic factors (including age, sex, race or ethnic background, height and weight, and occupation) and medical history, and subsequently reported any COVID-19 symptoms. We used Cox proportional hazards modelling to estimate multivariate-adjusted hazard ratios (HRs) of our primary outcome, which was a positive COVID-19 test. The COVID Symptom Study app is registered with ClinicalTrials.gov, NCT04331509. FINDINGS: Among 2 035 395 community individuals and 99 795 front-line health-care workers, we recorded 5545 incident reports of a positive COVID-19 test over 34 435 272 person-days. Compared with the general community, front-line health-care workers were at increased risk for reporting a positive COVID-19 test (adjusted HR 11·61, 95% CI 10·93-12·33). To account for differences in testing frequency between front-line health-care workers and the general community and possible selection bias, an inverse probability-weighted model was used to adjust for the likelihood of receiving a COVID-19 test (adjusted HR 3·40, 95% CI 3·37-3·43). Secondary and post-hoc analyses suggested adequacy of PPE, clinical setting, and ethnic background were also important factors. INTERPRETATION: In the UK and the USA, risk of reporting a positive test for COVID-19 was increased among front-line health-care workers. Health-care systems should ensure adequate availabili
Published: 2020

16. Exploratory Genome-Wide Interaction Analysis of Nonsteroidal Anti-inflammatory Drugs and Predicted Gene Expression on Colorectal Cancer Risk

Author: Wang, X, Su, Y-R, Petersen, PS, Bien, S, Schmit, SL, Drew, DA, Albanes, D, Berndt, S, Brenner, H, Campbell, PT, Casey, G, Cheng-Claude, J, Gallinger, S, Gruber, SB, Haile, RW, Harrison, TA, Hoffmeister, M, Jacobs, EJ, Jenkins, MA, Joshi, AD, Li, L, Lin, Y, Lindor, NM, Le Marchand, L, Martin, V, Milne, R, Maclnnis, R, Moreno, V, Nan, H, Newcomb, PA, Potter, JD, Rennert, G, Rennert, HS, Slattery, ML, Thibodeau, SN, Weinstein, SJ, Woods, MO, Chan, AT, White, E, Hsu, L, Peters, U, Wang, X, Su, Y-R, Petersen, PS, Bien, S, Schmit, SL, Drew, DA, Albanes, D, Berndt, S, Brenner, H, Campbell, PT, Casey, G, Cheng-Claude, J, Gallinger, S, Gruber, SB, Haile, RW, Harrison, TA, Hoffmeister, M, Jacobs, EJ, Jenkins, MA, Joshi, AD, Li, L, Lin, Y, Lindor, NM, Le Marchand, L, Martin, V, Milne, R, Maclnnis, R, Moreno, V, Nan, H, Newcomb, PA, Potter, JD, Rennert, G, Rennert, HS, Slattery, ML, Thibodeau, SN, Weinstein, SJ, Woods, MO, Chan, AT, White, E, Hsu, L, and Peters, U
Abstract: BACKGROUND: Regular use of nonsteroidal anti-inflammatory drugs (NSAID) is associated with lower risk of colorectal cancer. Genome-wide interaction analysis on single variants (G × E) has identified several SNPs that may interact with NSAIDs to confer colorectal cancer risk, but variations in gene expression levels may also modify the effect of NSAID use. Therefore, we tested interactions between NSAID use and predicted gene expression levels in relation to colorectal cancer risk. METHODS: Genetically predicted gene expressions were tested for interaction with NSAID use on colorectal cancer risk among 19,258 colorectal cancer cases and 18,597 controls from 21 observational studies. A Mixed Score Test for Interactions (MiSTi) approach was used to jointly assess G × E effects which are modeled via fixed interaction effects of the weighted burden within each gene set (burden) and residual G × E effects (variance). A false discovery rate (FDR) at 0.2 was applied to correct for multiple testing. RESULTS: Among the 4,840 genes tested, genetically predicted expression levels of four genes modified the effect of any NSAID use on colorectal cancer risk, including DPP10 (PG×E = 1.96 × 10-4), KRT16 (PG×E = 2.3 × 10-4), CD14 (PG×E = 9.38 × 10-4), and CYP27A1 (PG×E = 1.44 × 10-3). There was a significant interaction between expression level of RP11-89N17 and regular use of aspirin only on colorectal cancer risk (PG×E = 3.23 × 10-5). No interactions were observed between predicted gene expression and nonaspirin NSAID use at FDR < 0.2. CONCLUSIONS: By incorporating functional information, we discovered several novel genes that interacted with NSAID use. IMPACT: These findings provide preliminary support that could help understand the chemopreventive mechanisms of NSAIDs on colorectal cancer.
Published: 2020

17. Novel Common Genetic Susceptibility Loci for Colorectal Cancer

Author: Schmit, SL, Edlund, CK, Schumacher, FR, Gong, J, Harrison, TA, Huyghe, JR, Qu, C, Melas, M, Van den Berg, DJ, Wang, H, Tring, S, Plummer, SJ, Albanes, D, Alonso, MH, Amos, CI, Anton, K, Aragaki, AK, Arndt, V, Barry, EL, Berndt, SI, Bezieau, S, Bien, S, Bloomer, A, Boehm, J, Boutron-Ruault, M-C, Brenner, H, Brezina, S, Buchanan, DD, Butterbach, K, Caan, BJ, Campbell, PT, Carlson, CS, Castelao, JE, Chan, AT, Chang-Claude, J, Chanock, SJ, Cheng, I, Cheng, Y-W, Chin, LS, Church, JM, Church, T, Coetzee, GA, Cotterchio, M, Correa, MC, Curtis, KR, Duggan, D, Easton, DF, English, D, Feskens, EJM, Fischer, R, FitzGerald, LM, Fortini, BK, Fritsche, LG, Fuchs, CS, Gago-Dominguez, M, Gala, M, Gallinger, SJ, Gauderman, WJ, Giles, GG, Giovannucci, EL, Gogarten, SM, Gonzalez-Villalpando, C, Gonzalez-Villalpando, EM, Grady, WM, Greenson, JK, Gsur, A, Gunter, M, Haiman, CA, Hampe, J, Harlid, S, Harju, JF, Hayes, RB, Hofer, P, Hoffmeister, M, Hopper, JL, Huang, S-C, Huerta, JM, Hudson, TJ, Hunter, DJ, Idos, GE, Iwasaki, M, Jackson, RD, Jacobs, EJ, Jee, SH, Jenkins, MA, Jia, W-H, Jiao, S, Joshi, AD, Kolonel, LN, Kono, S, Kooperberg, C, Krogh, V, Kuehn, T, Kury, S, LaCroix, A, Laurie, CA, Lejbkowicz, F, Lemire, M, Lenz, H-J, Levine, D, Li, CI, Li, L, Lieb, W, Lin, Y, Lindor, NM, Liu, Y-R, Loupakis, F, Lu, Y, Luh, F, Ma, J, Mancao, C, Manion, FJ, Markowitz, SD, Martin, V, Matsuda, K, Matsuo, K, McDonnell, KJ, McNeil, CE, Milne, R, Molina, AJ, Mukherjee, B, Murphy, N, Newcomb, PA, Offit, K, Omichessan, H, Palli, D, Cotore, JPP, Perez-Mayoral, J, Pharoah, PD, Potter, JD, Raskin, L, Rennert, G, Rennert, HS, Riggs, BM, Schafmayer, C, Schoen, RE, Sellers, TA, Seminara, D, Severi, G, Shi, W, Shibata, D, Shu, X-O, Siegel, EM, Slattery, ML, Southey, M, Stadler, ZK, Stern, MC, Stintzing, S, Taverna, D, Thibodeau, SN, Thomas, DC, Trichopoulou, A, Tsugane, S, Ulrich, CM, van Duijnhoven, FJB, van Guelpan, B, Vijai, J, Virtamo, J, Weinstein, SJ, White, E, Win, AK, Wolk, A, Woods, M, Wu, AH, Wu, K, Xiang, Y-B, Yen, Y, Zanke, BW, Zeng, Y-X, Zhang, B, Zubair, N, Kweon, S-S, Figueiredo, JC, Zheng, W, Le Marchand, L, Lindblom, A, Moreno, V, Peters, U, Casey, G, Hsu, L, Conti, DV, Gruber, SB, Schmit, SL, Edlund, CK, Schumacher, FR, Gong, J, Harrison, TA, Huyghe, JR, Qu, C, Melas, M, Van den Berg, DJ, Wang, H, Tring, S, Plummer, SJ, Albanes, D, Alonso, MH, Amos, CI, Anton, K, Aragaki, AK, Arndt, V, Barry, EL, Berndt, SI, Bezieau, S, Bien, S, Bloomer, A, Boehm, J, Boutron-Ruault, M-C, Brenner, H, Brezina, S, Buchanan, DD, Butterbach, K, Caan, BJ, Campbell, PT, Carlson, CS, Castelao, JE, Chan, AT, Chang-Claude, J, Chanock, SJ, Cheng, I, Cheng, Y-W, Chin, LS, Church, JM, Church, T, Coetzee, GA, Cotterchio, M, Correa, MC, Curtis, KR, Duggan, D, Easton, DF, English, D, Feskens, EJM, Fischer, R, FitzGerald, LM, Fortini, BK, Fritsche, LG, Fuchs, CS, Gago-Dominguez, M, Gala, M, Gallinger, SJ, Gauderman, WJ, Giles, GG, Giovannucci, EL, Gogarten, SM, Gonzalez-Villalpando, C, Gonzalez-Villalpando, EM, Grady, WM, Greenson, JK, Gsur, A, Gunter, M, Haiman, CA, Hampe, J, Harlid, S, Harju, JF, Hayes, RB, Hofer, P, Hoffmeister, M, Hopper, JL, Huang, S-C, Huerta, JM, Hudson, TJ, Hunter, DJ, Idos, GE, Iwasaki, M, Jackson, RD, Jacobs, EJ, Jee, SH, Jenkins, MA, Jia, W-H, Jiao, S, Joshi, AD, Kolonel, LN, Kono, S, Kooperberg, C, Krogh, V, Kuehn, T, Kury, S, LaCroix, A, Laurie, CA, Lejbkowicz, F, Lemire, M, Lenz, H-J, Levine, D, Li, CI, Li, L, Lieb, W, Lin, Y, Lindor, NM, Liu, Y-R, Loupakis, F, Lu, Y, Luh, F, Ma, J, Mancao, C, Manion, FJ, Markowitz, SD, Martin, V, Matsuda, K, Matsuo, K, McDonnell, KJ, McNeil, CE, Milne, R, Molina, AJ, Mukherjee, B, Murphy, N, Newcomb, PA, Offit, K, Omichessan, H, Palli, D, Cotore, JPP, Perez-Mayoral, J, Pharoah, PD, Potter, JD, Raskin, L, Rennert, G, Rennert, HS, Riggs, BM, Schafmayer, C, Schoen, RE, Sellers, TA, Seminara, D, Severi, G, Shi, W, Shibata, D, Shu, X-O, Siegel, EM, Slattery, ML, Southey, M, Stadler, ZK, Stern, MC, Stintzing, S, Taverna, D, Thibodeau, SN, Thomas, DC, Trichopoulou, A, Tsugane, S, Ulrich, CM, van Duijnhoven, FJB, van Guelpan, B, Vijai, J, Virtamo, J, Weinstein, SJ, White, E, Win, AK, Wolk, A, Woods, M, Wu, AH, Wu, K, Xiang, Y-B, Yen, Y, Zanke, BW, Zeng, Y-X, Zhang, B, Zubair, N, Kweon, S-S, Figueiredo, JC, Zheng, W, Le Marchand, L, Lindblom, A, Moreno, V, Peters, U, Casey, G, Hsu, L, Conti, DV, and Gruber, SB
Abstract: 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: T
Published: 2019

18. Shared heritability and functional enrichment across six solid cancers

Author: Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboeller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, defazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Doerk, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuhl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Aguado-Barrera, ME, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, Mckay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, Lindstrom, S, Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboeller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, defazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Doerk, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuhl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Aguado-Barrera, ME, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, Mckay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, and Lindstrom, S
Abstract: Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10-8), breast and ovarian cancer (rg = 0.24, p = 7 × 10-5), breast and lung cancer (rg = 0.18, p =1.5 × 10-6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10-4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
Published: 2019

19. Discovery of common and rare genetic risk variants for colorectal cancer

Author: Huyghe, JR, Bien, SA, Harrison, TA, Kang, HM, Chen, S, Schmit, SL, Conti, DV, Qu, C, Jeon, J, Edlund, CK, Greenside, P, Wainberg, M, Schumacher, FR, Smith, JD, Levine, DM, Nelson, SC, Sinnott-Armstrong, NA, Albanes, D, Alonso, MH, Anderson, K, Arnau-Collell, C, Arndt, V, Bamia, C, Banbury, BL, Baron, JA, Berndt, SI, Bezieau, S, Bishop, DT, Boehm, J, Boeing, H, Brenner, H, Brezina, S, Buch, S, Buchanan, DD, Burnett-Hartman, A, Butterbach, K, Caan, BJ, Campbell, PT, Carlson, CS, Castellvi-Bel, S, Chan, AT, Chang-Claude, J, Chanock, SJ, Chirlaque, M-D, Cho, SH, Connolly, CM, Cross, AJ, Cuk, K, Curtis, KR, de la Chapelle, A, Doheny, KF, Duggan, D, Easton, DF, Elias, SG, Elliott, F, English, DR, Feskens, EJM, Figueiredo, JC, Fischer, R, FitzGerald, LM, Forman, D, Gala, M, Gallinger, S, Gauderman, WJ, Giles, GG, Gillanders, E, Gong, J, Goodman, PJ, Grady, WM, Grove, JS, Gsur, A, Gunter, MJ, Haile, RW, Hampe, J, Hampel, H, Harlid, S, Hayes, RB, Hofer, P, Hoffmeister, M, Hopper, JL, Hsu, W-L, Huang, W-Y, Hudson, TJ, Hunter, DJ, Ibanez-Sanz, G, Idos, GE, Ingersoll, R, Jackson, RD, Jacobs, EJ, Jenkins, MA, Joshi, AD, Joshu, CE, Keku, TO, Key, TJ, Kim, HR, Kobayashi, E, Kolonel, LN, Kooperberg, C, Kuehn, T, Kury, S, Kweon, S-S, Larsson, SC, Laurie, CA, Le Marchand, L, Leal, SM, Lee, SC, Lejbkowicz, F, Lemire, M, Li, CI, Li, L, Lieb, W, Lin, Y, Lindblom, A, Lindor, NM, Ling, H, Louie, TL, Mannisto, S, Markowitz, SD, Martin, V, Masala, G, McNeil, CE, Melas, M, Milne, RL, Moreno, L, Murphy, N, Myte, R, Naccarati, A, Newcomb, PA, Offit, K, Ogino, S, Onland-Moret, NC, Pardini, B, Parfrey, PS, Pearlman, R, Perduca, V, Pharoah, PDP, Pinchev, M, Platz, EA, Prentice, RL, Pugh, E, Raskin, L, Rennert, G, Rennert, HS, Riboli, E, Rodriguez-Barranco, M, Romm, J, Sakoda, LC, Schafmayer, C, Schoen, RE, Seminara, D, Shah, M, Shelford, T, Shin, M-H, Shulman, K, Sieri, S, Slattery, ML, Southey, MC, Stadler, ZK, Stegmaier, C, Su, Y-R, Tangen, CM, Thibodeau, SN, Thomas, DC, Thomas, SS, Toland, AE, Trichopoulou, A, Ulrich, CM, Van den Berg, DJ, van Duijnhoven, FJB, Van Guelpen, B, van Kranen, H, Vijai, J, Visvanathan, K, Vodicka, P, Vodickova, L, Vymetalkova, V, Weigl, K, Weinstein, SJ, White, E, Win, AK, Wolf, CR, Wolk, A, Woods, MO, Wu, AH, Zaidi, SH, Zanke, BW, Zhang, Q, Zheng, W, Scacheri, PC, Potter, JD, Bassik, MC, Kundaje, A, Casey, G, Moreno, V, Abecasis, GR, Nickerson, DA, Gruber, SB, Hsu, L, Peters, U, Huyghe, JR, Bien, SA, Harrison, TA, Kang, HM, Chen, S, Schmit, SL, Conti, DV, Qu, C, Jeon, J, Edlund, CK, Greenside, P, Wainberg, M, Schumacher, FR, Smith, JD, Levine, DM, Nelson, SC, Sinnott-Armstrong, NA, Albanes, D, Alonso, MH, Anderson, K, Arnau-Collell, C, Arndt, V, Bamia, C, Banbury, BL, Baron, JA, Berndt, SI, Bezieau, S, Bishop, DT, Boehm, J, Boeing, H, Brenner, H, Brezina, S, Buch, S, Buchanan, DD, Burnett-Hartman, A, Butterbach, K, Caan, BJ, Campbell, PT, Carlson, CS, Castellvi-Bel, S, Chan, AT, Chang-Claude, J, Chanock, SJ, Chirlaque, M-D, Cho, SH, Connolly, CM, Cross, AJ, Cuk, K, Curtis, KR, de la Chapelle, A, Doheny, KF, Duggan, D, Easton, DF, Elias, SG, Elliott, F, English, DR, Feskens, EJM, Figueiredo, JC, Fischer, R, FitzGerald, LM, Forman, D, Gala, M, Gallinger, S, Gauderman, WJ, Giles, GG, Gillanders, E, Gong, J, Goodman, PJ, Grady, WM, Grove, JS, Gsur, A, Gunter, MJ, Haile, RW, Hampe, J, Hampel, H, Harlid, S, Hayes, RB, Hofer, P, Hoffmeister, M, Hopper, JL, Hsu, W-L, Huang, W-Y, Hudson, TJ, Hunter, DJ, Ibanez-Sanz, G, Idos, GE, Ingersoll, R, Jackson, RD, Jacobs, EJ, Jenkins, MA, Joshi, AD, Joshu, CE, Keku, TO, Key, TJ, Kim, HR, Kobayashi, E, Kolonel, LN, Kooperberg, C, Kuehn, T, Kury, S, Kweon, S-S, Larsson, SC, Laurie, CA, Le Marchand, L, Leal, SM, Lee, SC, Lejbkowicz, F, Lemire, M, Li, CI, Li, L, Lieb, W, Lin, Y, Lindblom, A, Lindor, NM, Ling, H, Louie, TL, Mannisto, S, Markowitz, SD, Martin, V, Masala, G, McNeil, CE, Melas, M, Milne, RL, Moreno, L, Murphy, N, Myte, R, Naccarati, A, Newcomb, PA, Offit, K, Ogino, S, Onland-Moret, NC, Pardini, B, Parfrey, PS, Pearlman, R, Perduca, V, Pharoah, PDP, Pinchev, M, Platz, EA, Prentice, RL, Pugh, E, Raskin, L, Rennert, G, Rennert, HS, Riboli, E, Rodriguez-Barranco, M, Romm, J, Sakoda, LC, Schafmayer, C, Schoen, RE, Seminara, D, Shah, M, Shelford, T, Shin, M-H, Shulman, K, Sieri, S, Slattery, ML, Southey, MC, Stadler, ZK, Stegmaier, C, Su, Y-R, Tangen, CM, Thibodeau, SN, Thomas, DC, Thomas, SS, Toland, AE, Trichopoulou, A, Ulrich, CM, Van den Berg, DJ, van Duijnhoven, FJB, Van Guelpen, B, van Kranen, H, Vijai, J, Visvanathan, K, Vodicka, P, Vodickova, L, Vymetalkova, V, Weigl, K, Weinstein, SJ, White, E, Win, AK, Wolf, CR, Wolk, A, Woods, MO, Wu, AH, Zaidi, SH, Zanke, BW, Zhang, Q, Zheng, W, Scacheri, PC, Potter, JD, Bassik, MC, Kundaje, A, Casey, G, Moreno, V, Abecasis, GR, Nickerson, DA, Gruber, SB, Hsu, L, and Peters, U
Abstract: 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 ~100. New signals implicate lower-frequency variants, Krüppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.
Published: 2019

20. Shared heritability and functional enrichment across six solid cancers (vol 10, 431, 2019)

Author: Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, deFazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Dork, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuehl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Elias Aguado-Barrera, M, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, McKay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, Lindstrom, S, Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, deFazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Dork, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuehl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Elias Aguado-Barrera, M, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, McKay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, and Lindstrom, S
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2019

21. Mendelian randomization analysis of C-reactive protein on colorectal cancer risk

Author: Wang, X, Dai, JY, Albanes, D, Arndt, V, Berndt, SI, Bezieau, S, Brenner, H, Buchanan, DD, Butterbach, K, Caan, B, Casey, G, Campbell, PT, Chan, AT, Chen, Z, Chang-Claude, J, Cotterchio, M, Easton, DF, Giles, GG, Giovannucci, E, Grady, WM, Hoffmeister, M, Hopper, JL, Hsu, L, Jenkins, MA, Joshi, AD, Lampe, JW, Larsson, SC, Lejbkowicz, F, Li, L, Lindblom, A, Le Marchand, L, Martin, V, Milne, RL, Moreno, V, Newcomb, PA, Offitt, K, Ogino, S, Pharoah, PDP, Pinchev, M, Potter, JD, Rennert, HS, Rennert, G, Saliba, W, Schafmayer, C, Schoen, RE, Schrotz-King, P, Slattery, ML, Song, M, Stegmaier, C, Weinstein, SJ, Wolk, A, Woods, MO, Wu, AH, Gruber, SB, Peters, U, White, E, Wang, X, Dai, JY, Albanes, D, Arndt, V, Berndt, SI, Bezieau, S, Brenner, H, Buchanan, DD, Butterbach, K, Caan, B, Casey, G, Campbell, PT, Chan, AT, Chen, Z, Chang-Claude, J, Cotterchio, M, Easton, DF, Giles, GG, Giovannucci, E, Grady, WM, Hoffmeister, M, Hopper, JL, Hsu, L, Jenkins, MA, Joshi, AD, Lampe, JW, Larsson, SC, Lejbkowicz, F, Li, L, Lindblom, A, Le Marchand, L, Martin, V, Milne, RL, Moreno, V, Newcomb, PA, Offitt, K, Ogino, S, Pharoah, PDP, Pinchev, M, Potter, JD, Rennert, HS, Rennert, G, Saliba, W, Schafmayer, C, Schoen, RE, Schrotz-King, P, Slattery, ML, Song, M, Stegmaier, C, Weinstein, SJ, Wolk, A, Woods, MO, Wu, AH, Gruber, SB, Peters, U, and White, E
Abstract: BACKGROUND: Chronic inflammation is a risk factor for colorectal cancer (CRC). Circulating C-reactive protein (CRP) is also moderately associated with CRC risk. However, observational studies are susceptible to unmeasured confounding or reverse causality. Using genetic risk variants as instrumental variables, we investigated the causal relationship between genetically elevated CRP concentration and CRC risk, using a Mendelian randomization approach. METHODS: Individual-level data from 30 480 CRC cases and 22 844 controls from 33 participating studies in three international consortia were used: the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), the Colorectal Transdisciplinary Study (CORECT) and the Colon Cancer Family Registry (CCFR). As instrumental variables, we included 19 single nucleotide polymorphisms (SNPs) previously associated with CRP concentration. The SNP-CRC associations were estimated using a logistic regression model adjusted for age, sex, principal components and genotyping phases. An inverse-variance weighted method was applied to estimate the causal effect of CRP on CRC risk. RESULTS: Among the 19 CRP-associated SNPs, rs1260326 and rs6734238 were significantly associated with CRC risk (P = 7.5 × 10-4, and P = 0.003, respectively). A genetically predicted one-unit increase in the log-transformed CRP concentrations (mg/l) was not associated with increased risk of CRC [odds ratio (OR) = 1.04; 95% confidence interval (CI): 0.97, 1.12; P = 0.256). No evidence of association was observed in subgroup analyses stratified by other risk factors. CONCLUSIONS: In spite of adequate statistical power to detect moderate association, we found genetically elevated CRP concentration was not associated with increased risk of CRC among individuals of European ancestry. Our findings suggested that circulating CRP is unlikely to be a causal factor in CRC development.
Published: 2019

22. Factors associated with oxidative stress and cancer risk in the Breast and Prostate Cancer Cohort Consortium

Author: Blein, S, Berndt, S, Joshi, Ad, Campa, D, Ziegler, Rg, Riboli, E, Cox, Dg, Gaudet, Mm, Stevens, Vl, Diver, Wr, Gapstur, Sm, Chanock, Sj, Hoover, Rn, Yeager, M, Albanes, D, Virtamo, J, Crawford, Ed, Isaacs, C, Berg, C, Trichopoulos, D, Peeters, Ph, Johansson, M, Khaw, Kt, Kraft, P, Hunter, Dj, Lindström, S, Ma, J, Stampfer, M, Gaziano, Jm, Giovannucci, E, Willett, Wh, Hankinson, Se, Lee, Im, Buring, J, Henderson, B, Marchand, Ll, Kolonel, L, Haiman, C.j., PANICO, SALVATORE, Blein, S, Berndt, S, Joshi, Ad, Campa, D, Ziegler, Rg, Riboli, E, Cox, Dg, Gaudet, Mm, Stevens, Vl, Diver, Wr, Gapstur, Sm, Chanock, Sj, Hoover, Rn, Yeager, M, Albanes, D, Virtamo, J, Crawford, Ed, Isaacs, C, Berg, C, Trichopoulos, D, Panico, Salvatore, Peeters, Ph, Johansson, M, Khaw, Kt, Kraft, P, Hunter, Dj, Lindström, S, Ma, J, Stampfer, M, Gaziano, Jm, Giovannucci, E, Willett, Wh, Hankinson, Se, Lee, Im, Buring, J, Henderson, B, Marchand, Ll, Kolonel, L, and Haiman, C. j.
Subjects: MnSOD, Male, Oncology, medicine.medical_specialty, Genotype, Biology, medicine.disease_cause, Polymorphism, Single Nucleotide, Biochemistry, Prostate cancer, Breast cancer, Prostate, Internal medicine, Epidemiology, medicine, Genetic Predisposition to Disease, Breast, Survival analysis, Gynecology, Medicine (all), Oxidative Stre, General Medicine, medicine.disease, Mitochondria, medicine.anatomical_structure, Alcohol, GPX-1, Prostatic Neoplasm, Cohort, Female, Survival Analysi, Reactive Oxygen Specie, Breast Neoplasm, Oxidative stress, Human
Abstract: Both endogenous factors (genomic variations) and exogenous factors (environmental exposures, lifestyle) impact the balance of reactive oxygen species (ROS). Variants of the ND3 (rs2853826; G10398A) gene of the mitochondrial genome, manganese superoxide dismutase (MnSOD; rs4880 Val16Ala) and glutathione peroxidase (GPX-1; rs1050450 Pro198Leu), are purported to have functional effects on regulation of ROS balance. In this study, we examined associations of breast and prostate cancer risks and survival with these variants, and interactions between rs4880-rs1050450, and alcohol consumption-rs2853826. Nested case-control studies were conducted in the Breast and Prostate Cancer Cohort Consortium (BPC3), consisting of nine cohorts. The analyses included over 10726 post-menopausal breast and 7532 prostate cancer cases with matched controls. Logistic regression models were used to evaluate associations with risk, and proportional hazard models were used for survival outcomes. We did not observe significant interactions between polymorphisms in MnSOD and GPX-1, or between mitochondrial polymorphisms and alcohol intake and risk of either breast (p-interaction of 0.34 and 0.98, respectively) or prostate cancer (p-interaction of 0.49 and 0.50, respectively). We observed a weak inverse association between prostate cancer risk and GPX-1 Leu198Leu carriers (OR 0.87, 95% CI 0.79-0.97, p = 0.01). Overall survival among women with breast cancer was inversely associated with G10398 carriers who consumed alcohol (HR 0.66 95% CI 0.49-0.88). Given the high power in our study, it is unlikely that interactions tested have more than moderate effects on breast or prostate cancer risk. Observed associations need both further epidemiological and biological confirmation.
Published: 2014

23. Evidence for large-scale gene-by-smoking interaction effects on pulmonary function

Author: Aschard, H, Tobin, MD, Hancock, DB, Skurnik, D, Sood, A, James, A, Smith, AV, Manichaikul, A, Campbell, A (Archie), Prins, BP, Hayward, C, Loth, Daan, Porteous, DJ, Strachan, DP, Zeggini, E, O'Connor, GT, Brusselle, Guy, Boezen, HM, Schulz, H, Deary, IJ, Hall, IP, Rudan, I, Kaprio, J, Wilson, JF, Wilk, JB, Huffman, JE, Zhao, JH, de Jong, K, Lyytikainen, LP, Wain, LV, Jarvelin, MR, Kahonen, M, Fornage, M, Polasek, O, Cassano, PA, Barr, RG, Rawal, R, Harris, SE, Gharib, SA, Enroth, S, Heckbert, SR, Lehtimaki, T, Gyllensten, U, Jackson, VE, Gudnason, V, Tang, WB, Dupuis, J, Artigas, MS, Joshi, AD, London, SJ, Kraft, P, Aschard, H, Tobin, MD, Hancock, DB, Skurnik, D, Sood, A, James, A, Smith, AV, Manichaikul, A, Campbell, A (Archie), Prins, BP, Hayward, C, Loth, Daan, Porteous, DJ, Strachan, DP, Zeggini, E, O'Connor, GT, Brusselle, Guy, Boezen, HM, Schulz, H, Deary, IJ, Hall, IP, Rudan, I, Kaprio, J, Wilson, JF, Wilk, JB, Huffman, JE, Zhao, JH, de Jong, K, Lyytikainen, LP, Wain, LV, Jarvelin, MR, Kahonen, M, Fornage, M, Polasek, O, Cassano, PA, Barr, RG, Rawal, R, Harris, SE, Gharib, SA, Enroth, S, Heckbert, SR, Lehtimaki, T, Gyllensten, U, Jackson, VE, Gudnason, V, Tang, WB, Dupuis, J, Artigas, MS, Joshi, AD, London, SJ, and Kraft, P
Published: 2017

24. THU0753-HPR Predicting the future development of spondyloarthritis among patients with idiopathic acute anterior uveitis using real-world data

Author: Haroon, M, primary, Betts, KA, additional, Mu, F, additional, Skup, M, additional, Anderson, JK, additional, and Joshi, AD, additional
Published: 2017
Full Text: View/download PDF

25. Florbetapir F 18 amyloid PET and 36-month cognitive decline: a prospective multicenter study

Author: Doraiswamy, PM, Sperling, RA, Johnson, K, Reiman, EM, Wong, TZ, Sabbagh, MN, Sadowsky, CH, Fleisher, AS, Carpenter, A, Joshi, AD, Lu, M, Grundman, M, Mintun, MA, Skovronsky, DM, Pontecorvo, MJ, and AV45-A11 Study Group
Subjects: Male, Aging, Clinical Trials and Supportive Activities, Neuropsychological Tests, Neurodegenerative, Alzheimer's Disease, Medical and Health Sciences, AV45-A11 Study Group, Alzheimer Disease, Clinical Research, Acquired Cognitive Impairment, Humans, 2.1 Biological and endogenous factors, Cognitive Dysfunction, Longitudinal Studies, Prospective Studies, Aetiology, Nootropic Agents, Aged, Psychiatry, Aniline Compounds, Amyloid beta-Peptides, Psychology and Cognitive Sciences, Neurosciences, Brain, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), amyloid, Biological Sciences, cognitive decline, MCI, Brain Disorders, PET, Positron-Emission Tomography, Neurological, Disease Progression, florbetapir, Ethylene Glycols, Female, Dementia, Radiopharmaceuticals, Follow-Up Studies
Abstract: This study was designed to evaluate whether subjects with amyloid beta (Aβ) pathology, detected using florbetapir positron emission tomorgraphy (PET), demonstrated greater cognitive decline than subjects without Aβ pathology. Sixty-nine cognitively normal (CN) controls, 52 with recently diagnosed mild cognitive impairment (MCI) and 31 with probable Alzheimer's disease (AD) dementia were included in the study. PET images obtained in these subjects were visually rated as positive (Aβ+) or negative (Aβ-), blind to diagnosis. Fourteen percent (10/69) of CN, 37% (19/52) of MCI and 68% (21/31) of AD were Aβ+. The primary outcome was change in ADAS-Cog score in MCI subjects after 36 months; however, additional outcomes included change on measures of cognition, function and diagnostic status. Aβ+ MCI subjects demonstrated greater worsening compared with Aβ- subjects on the ADAS-Cog over 36 months (5.66 ± 1.47 vs -0.71 ± 1.09, P = 0.0014) as well as on the mini-mental state exam (MMSE), digit symbol substitution (DSS) test, and a verbal fluency test (P < 0.05). Similar to MCI subjects, Aβ+ CN subjects showed greater decline on the ADAS-Cog, digit-symbol-substitution test and verbal fluency (P
Published: 2014

26. COMPREHENSIVE ANALYSES OF DNA REPAIR PATHWAYS, SMOKING, AND BLADDER CANCER RISK IN LOS ANGELES AND SHANGHAI

Author: Corral, R, Lewinger, JP, Van den Berg, D, Joshi, AD, Yuan, JM, Gago Dominguez, Manuela, Cortessis, VK, Pike, MC, Conti, DV, Thomas, DC, Edlund, CK, Gao, YT, Xiang, YB, Zhang, W, Su, YC, and Stern, MC
Subjects: Adult, Male, Carcinoma, Transitional Cell, China, DNA Repair, Smoking, Antigens, Nuclear, Middle Aged, Los Angeles, Polymorphism, Single Nucleotide, Article, DNA-Binding Proteins, Urinary Bladder Neoplasms, Risk Factors, Humans, Female, Genetic Predisposition to Disease, Ku Autoantigen, Aged, Sterol Regulatory Element Binding Protein 2
Abstract: Tobacco smoking is a bladder cancer risk factor and a source of carcinogens that induce DNA damage to urothelial cells. Using data and samples from 988 cases and 1,004 controls enrolled in the Los Angeles County Bladder Cancer Study and the Shanghai Bladder Cancer Study, we investigated associations between bladder cancer risk and 632 tagSNPs that comprehensively capture genetic variation in 28 DNA repair genes from four DNA repair pathways: base excision repair (BER), nucleotide excision repair (NER), non-homologous end-joining (NHEJ) and homologous recombination repair (HHR). Odds ratios (ORs) and 95% confidence intervals (CIs) for each tagSNP were corrected for multiple testing for all SNPs within each gene using pACT and for genes within each pathway and across pathways with Bonferroni. Gene and pathway summary estimates were obtained using ARTP. We observed an association between bladder cancer and POLB rs7832529 (BER) (pACT = 0.003; ppathway = 0.021) among all, and SNPs in XPC (NER) and OGG1 (BER) among Chinese men and women, respectively. The NER pathway showed an overall association with risk among Chinese males (ARTP NER p = 0.034). The XRCC6 SNP rs2284082 (NHEJ), also in LD with SREBF2, showed an interaction with smoking (smoking status interaction pgene = 0.001, ppathway = 0.008, poverall = 0.034). Our findings support a role in bladder carcinogenesis for regions that map close to or within BER (POLB, OGG1) and NER genes (XPC). A SNP that tags both the XRCC6 and SREBF2 genes strongly modifies the association between bladder cancer risk and smoking.
Published: 2014

27. Amyloid imaging and cognitive decline in nondemented oldest-old: The 90+ Study

Author: Kawas, CH, Greenia, DE, Bullain, SS, Clark, CM, Pontecorvo, MJ, Joshi, AD, and Corrada, MM
Abstract: Background: The goal of this study was to examine cross-sectional and longitudinal associations between cognitive performance and beta amyloid (Aβ) load determined by florbetapir F18 positron emission tomography (PET) in nondemented oldest-old. Methods: Thirteen nondemented (normal or cognitively impaired nondemented) participants (median age, 94.2 years) from The 90+ Study underwent florbetapir-PET scanning within 3 months of baseline neuropsychological testing. Amyloid load was measured with a semi-automated quantitative analysis of average cortical-to-cerebellar standardized uptake value ratio (SUVr) and a visual interpretation (Aβ- or Aβ+). Neuropsychological testing was repeated every 6 months. Results: At baseline, SUVr correlated significantly with tests of global cognition and memory. During follow-up (median, 1.5 years), the Aβ+ group had steeper declines on most cognitive tests, particularly global cognitive measures. Conclusion: This preliminary study suggests that greater amyloid load is associated with poorer cognition and faster cognitive decline in nondemented oldest-old. Amyloid load may identify individuals at increased risk of developing Alzheimer's disease. © 2013 The Alzheimer's Association. All rights reserved.
Published: 2013

28. Amyloid Imaging with Florbetapir-PET Correlates with Cognitive Performance in Non-Demented Oldest-Old

Author: Corrada, MM, Greenia, DE, Clark, CM, Peltz, CB, Mintun, MA, Pontecorvo, MJ, Joshi, AD, and Kawas, CH
Published: 2011

29. Prognostic value of 8F-Florbetapir scan: a 36-month follow up analysis using ADNI data

Author: Lu, M, primary, Pontecorvo, M, additional, Siderowf, A, additional, Joshi, AD, additional, Devous, MD, additional, Mintun, MA, additional, and Montoya, A, additional
Published: 2015
Full Text: View/download PDF

30. Polymorphisms in DNA repair genes, smoking, and bladder cancer risk: findings from the International Consortium of Bladder Cancer

Author: Stern, Mc, Lin, J, Figueroa, Jd, Kelsey, Kt, Kiltie, Ae, Yuan, J. M., Matullo, G, Fletcher, T, Benhamou, S, Taylor, Ja, Placidi, Donatella, Zhang, Zf, Steineck, G, Rothman, N, Kogevinas, M, Silverman, D, Malatas, N, Chanock, S, Wu, X, KARAGAS MR ANDREW AS, Nelson, Hh, Bishop, Dt, Sak, Sc, Choudhury, A, Barrett, Jh, Elliot, F, Corral, R, Joshi, Ad, GAGO DOMINGUEZ, M, Cortessis, Vk, Xiang, Yb, Vineis, P, Sacerdote, C, Guarrera, S, Polidoro, S, Allione, A, Gurzau, E, Koppova, K, Kumar, R, Rudnai, P, Porru, Stefano, Carta, Angela, Campagna, Marcello, Arici, Cecilia, Park, Sl, and GARCIA CLOSAS, M.
Published: 2009

31. Glioblastoma cell growth is suppressed by disruption of fibroblast growth factor pathway signaling

Author: Loilome, W, Joshi, A, ap Rhys, C, Piccirillo, S, Vescovi, A, Gallia, G, Riggins, G, Joshi, AD, ap Rhys, CM, Gallia, GL, Riggins, GJ, VESCOVI, ANGELO LUIGI, Loilome, W, Joshi, A, ap Rhys, C, Piccirillo, S, Vescovi, A, Gallia, G, Riggins, G, Joshi, AD, ap Rhys, CM, Gallia, GL, Riggins, GJ, and VESCOVI, ANGELO LUIGI
Abstract: The Fibroblast Growth Factor (FGF) signaling pathway is reported to stimulate glioblastoma (GBM) growth. In this work we evaluated the effect of FGF2, FGF receptor (FGFR), and small molecule inhibition on GBM cells grown in traditional media, or cultured directly in stem-cell media. These lines each expressed the FGFR1, FGFR3 and FGFR4 receptors. Addition of FGF2 ligand showed significant growth stimulation in 8 of 10 cell lines. Disruption of FGF signaling by a neutralizing FGF2 monoclonal antibody and FGFR1 suppression by RNA interference both partially inhibited cell proliferation. Growth inhibition was temporally correlated with a reduction in MAPK signaling. A receptor tyrosine kinase inhibitor with known FGFR/VEGFR activity, PD173074, showed reproducible growth inhibition. Possible mechanisms of growth suppression by PD173074 were implicated by reduced phosphorylation of AKT and MAPK, known oncogenic signal transducers. Subsequent reduction in the cyclin D1, cyclin D2 and CDK4 cell cycle regulators was also observed. Our results indicate that FGF signaling pathway inhibition as a monotherapy will slow, but not arrest growth of glioblastoma cells. © Springer Science+Business Media, LLC. 2009.
Published: 2009

32. Abstract P3-04-03: Combined Epigenetic Targeting Reverses Epithelial-Mesencymal Transition (EMT) and Reduces Invasiveness of Human Breast Cancer Cells

Author: Joshi, AD, primary, Rao, R, additional, Fiskus, W, additional, Buckley, KM, additional, Nalluri, S, additional, Balusu, R, additional, Atadja, P, additional, and Bhalla, KN., additional
Published: 2010
Full Text: View/download PDF

33. Drowsiness Detection using EEG signals and Machine Learning Algorithms

Author: Joshi Adinath, Kamble Atharva, Parate Akanksha, Parkar Siddhesh, Puri Digambar, and Gaikwad Chandrakant
Subjects: Information technology, T58.5-58.64
Abstract: Drowsiness is described as a state of reduced consciousness and vigilance accompanied by a desire or want to sleep. Driver tiredness is frequently detected using wearable sensors that track vehicle movement and camera-based systems that track driver behavior. Many alternative EEG-based drowsiness detection systems are developed due to the potential of electroencephalogram (EEG) signals to observe human mood and the ease with which they may be obtained. This paper applies Deep learning architecture like Convolutional Neural networks (CNN) and algorithms for the classification of EEG data for Drowsiness Detection. The key measures of video-based approaches include the detection of physical features; nevertheless, problems such as brightness limitations and practical challenges such as driver attention limits its usefulness. The main measure of video-based methods is the degree of closure of the eyelids; however, its success is limited by constraints like as brightness restrictions and practical challenges such as driver distraction. We have extracted statistical features and trained using various classifiers like Logistic Regression, Naïve Bayes, SVM, and K Nearest Neighbours and compared the accuracy using a deep learning CNN model. Results demonstrate that CNN achieved an accuracy of 94.75% by delegating feature extraction on itself. Upon comparing existing state–of–the–art drowsiness detection systems, the testing results reveal a higher detection capability. The results show that the the suggested method can be used to develop a reliable EEG-based driving drowsiness detection system.
Published: 2022
Full Text: View/download PDF

34. Cognition and amyloid load in Alzheimer disease imaged with florbetapir F 18(AV-45) positron emission tomography.

Author: Rosenberg PB, Wong DF, Edell SL, Ross JS, Joshi AD, Brasic JR, Zhou Y, Raymont V, Kumar A, Ravert HT, Dannals RF, Pontecorvo MJ, Skovronsky DM, Lyketsos CG, Rosenberg, Paul B, Wong, D F, Edell, S L, Ross, J S, Joshi, A D, and Brašić, J R
Abstract: Objective: To examine the association between regional brain uptake of a novel amyloid positron emission tomography (PET) tracer florbetapir F 18 ([(18)F]-AV-45) and cognitive performance in a pilot study.Design: Cross-sectional comparison of [(18)F]-AV-45 in AD patients versus controls.Setting: Three specialty memory clinics.Participants: Eleven participants with probable Alzheimer disease (AD) by NINDS/ADRDA criteria and 15 healthy comparison (HC) participants.Measurements: Participants underwent PET imaging following a 370 MBq (10 mCi) intravenous administration of [(18)F]-AV-45. Regional/cerebellar standardized uptake value ratios (SUVRs) were calculated. Cognition was assessed using Mini-Mental State Examination, Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog), Wechsler Logical Memory IA (immediate recall) test (LMIA), and verbal category fluency.Results: Greater [(18)F]-AV-45 SUVR was associated with poorer performance on all cognitive tests. In the HC group, occipital, parietal, precuneus, temporal, and cortical average SUVR was associated with greater ADAS-Cog, and greater anterior cingulate SUVR was associated with lower LMIA. Two HC participants had [(18)F]-AV-45 cortical/cerebellar SUVR greater than 1.5, one of whom had deficits in episodic recall and on follow-up met criteria for amnestic mild cognitive impairment.Conclusion: [(18)F]-AV-45 SUVR in several brain regions was associated with worse global cognitive performance particularly in HC, suggesting its potential as a marker of preclinical AD. [ABSTRACT FROM AUTHOR]
Published: 2013
Full Text: View/download PDF

35. Amyloid-β assessed by florbetapir F 18 PET and 18-month cognitive decline: a multicenter study.

Author: Doraiswamy PM, Sperling RA, Coleman RE, Johnson KA, Reiman EM, Davis MD, Grundman M, Sabbagh MN, Sadowsky CH, Fleisher AS, Carpenter A, Clark CM, Joshi AD, Mintun MA, Skovronsky DM, Pontecorvo MJ, AV45-A11 Study Group, Doraiswamy, P Murali, Sperling, Reisa A, and Coleman, R Edward
Published: 2012
Full Text: View/download PDF

36. Volumetric facelift: evaluation of rhytidectomy with alloplastic augmentation.

Author: Hopping SB, Joshi AD, Tanna N, and Janjanin S
Abstract: Loss of soft tissue volume and laxity of the overlying skin. Volumetric augmentation is a key component of facial rejuvenation surgery, and should be considered of equal importance to soft tissue lifting. Augmentation can be accomplished with synthetic fillers, autologous grafts, soft tissue repositioning techniques, and/or alloplastic implants. Only alloplastic implants, however, provide truly long-term volumetric correction. To date, there have been no large series dealing with the complications and results of implantation performed concurrently with rhytidectomy, which we have termed 'volumetric rhytidectomy.' We present our experience with 100 patients treated with a combination of malar and chin implants and rhytidectomy, compared to 200 patients who underwent rhytidectomy alone. Methods: The authors performed a retrospective review of patients treated with a combination of silicone malar and chin augmentation with rhytidectomy versus patients treated with rhytidectomy alone. Both groups of patients underwent close postoperative evaluation at 3 days, 1 week, 2 weeks, and 1 month. All patients were surveyed at 6 months to assess aesthetic satisfaction. Complication rates were noted and tabulated. Statistical analysis was performed to evaluate for any differences in the two groups. Results: Between 2002 and 2006, 100 patients underwent malar and chin implantation along with rhytidectomy; 200 patients underwent rhytidectomy alone. In the first group, there were a total of 6 cases in which implant removal was necessary, and 2 cases in which revision was required. There were no statistically significant differences (p < 0.05) observed between the two groups with respect to major or minor hematoma, seroma, infection, sensory nerve injury, facial nerve injury, hypertrophic scarring, dehiscence, skin sloughing, or revision. Conclusions: Volumetric rhytidectomy reliably augments the malar and mental areas, allows for subtle skeletal contouring, and results in successful rejuvenation. Rhytidectomy is relatively safe to perform concurrently with silicone augmentation, and does not result in an increased complication rate as compared to rhytidectomy alone. [ABSTRACT FROM AUTHOR]
Published: 2010
Full Text: View/download PDF

37. Toll-like receptor 9 activation is a key mechanism for the maintenance of chronic lung inflammation.

Author: Ito T, Schaller M, Raymond T, Joshi AD, Coelho AL, Frantz FG, Carson WF 4th, Hogaboam CM, Lukacs NW, Standiford TJ, Phan SH, Chensue SW, Kunkel SL, Ito, Toshihiro, Schaller, Matthew, Raymond, Tracy, Joshi, Amrita D, Coelho, Ana L, Frantz, Fabiani G, and Carson, William F 4th
Abstract: Rationale: Accumulating evidence supports the hypothesis that the continuous host response to a persistent challenge can polarize the cytokine environment toward a Th2 cytokine phenotype, but the mechanisms responsible for this skewing are not clear.Objectives: We investigated the role of Toll-like receptor 9 (TLR9) in a Th2-driven pulmonary granulomatous response initiated via the embolization of Schistosoma mansoni eggs to the lungs of mice.Methods: Mice were intravenously injected with S. mansoni eggs. Histological and flow cytometric analysis, cytokine measurement, adoptive transfer of bone marrow (BM)-derived dendritic cells (DCs), and in vitro T-cell treatments with antigen-presenting cells were examined.Measurements and Main Results: In comparison to wild-type mice, TLR9(-/-) mice showed increased pulmonary granuloma size, augmented collagen deposition, increased Th2 cytokine phenotype, and impaired accumulation of DCs. BM-derived DCs, but not macrophages, recovered from animals with developed Th2-type lung granulomas promoted the production of type 2 cytokines from CD4(+) T cells. BM-derived DCs from TLR9(-/-) mice induced impaired Th1 cytokine and enhanced Th2 cytokine production by T cells, compared with DCs from WT mice. Macrophages from TLR9(-/-) mice expressed a significantly higher alternatively activated (M2) phenotype characterized by increased "found in inflammatory zone-1" (FIZZ1) and arginase-1 expression. The adoptive transfer of BM-derived DCs from syngeneic WT mice into TLR9(-/-) mice restored the granuloma phenotype seen in WT mice.Conclusions: These studies suggest that TLR9 plays an important mechanistic role in the maintenance of the pulmonary granulomatous response. [ABSTRACT FROM AUTHOR]
Published: 2009
Full Text: View/download PDF

38. Novel metabolomic predictors of incident colorectal cancer in men and women.

Author: Downie JM, Joshi AD, Geraghty CM, Guercio BJ, Zeleznik OA, Song M, Bever AM, Drew DA, Tabung FK, Zhang X, Jin L, Eliassen AH, Willett WC, Wu K, Kraft P, Tamimi R, Clish C, Fuchs CS, Giovannucci E, Meyerhardt JA, and Chan AT
Abstract: Background: Metabolomic profiles may influence colorectal cancer (CRC) development. Few studies have performed pre-diagnostic metabolome-wide analyses with CRC risk., Methods: We conducted a nested case-control study among women (Nurses' Health Study (NHS)) and men (Health Professionals Follow-up Study (HPFS)) who provided blood between 1989 and 1995. Over 22.9 years, 684 (409 NHS, 275 HPFS) incident CRC cases occurred and were matched 1:1 to controls. Liquid chromatography-mass spectrometry (LC-MS) identified 255 plasma metabolites after quality control. Cohort-specific and combined metabolite association analyses were performed using conditional logistic regression. Metabolite set enrichment analysis (MSEA) was used to identify differential abundance in metabolite classes. Weighted Correlation Network Analysis (WGCNA) provided modules of covarying metabolites, which were tested for CRC association., Results: MSEA identified specific acylcarnitines associated with higher CRC risk and triacylglycerols with lower CRC risk among women and men. Further, phosphatidylcholines were associated with a higher risk of CRC among men. In an analysis restricted to CRC cases diagnosed two years after blood draw, myristoleic acid (OR = 1.37; 95%CI = 1.15-1.62; FDR = 0.072) and C60:12 triacylglycerol (OR = 0.75; 95%CI = 0.64-0.88; FDR = 0.072 were associated with CRC risk in women. WGCNA identified amino acids associated with CRC in men, fatty acid esters (carnitines) with distal CRC in men, and triradylcglycerols inversely associated with CRC in women., Conclusions: We identified pre-diagnostic CRC-associated metabolites with distinct sex-specific profiles. These results provide insight into CRC etiopathogenesis and have implications for risk prediction strategies., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
Published: 2024
Full Text: View/download PDF

39. The STAT3/SETDB2 axis dictates NF-κB-mediated inflammation in macrophages during wound repair.

Author: Mangum KD, denDekker A, Li Q, Tsoi LC, Joshi AD, Melvin WJ, Wolf SJ, Moon JY, Audu CO, Shadiow J, Obi AT, Wasikowski R, Barrett EC, Bauer TM, Boyer K, Ahmed Z, Davis FM, Gudjonsson J, and Gallagher KA
Subjects: Animals, Humans, Male, Mice, Gene Expression Regulation, Mice, Inbred C57BL, Mice, Knockout, Transcription Factor RelA metabolism, Transcription Factor RelA genetics, Histone-Lysine N-Methyltransferase metabolism, Histone-Lysine N-Methyltransferase genetics, Inflammation metabolism, Inflammation genetics, Inflammation pathology, Macrophages metabolism, Macrophages immunology, NF-kappa B metabolism, STAT3 Transcription Factor metabolism, STAT3 Transcription Factor genetics, Wound Healing genetics
Abstract: Macrophage transition from an inflammatory to reparative phenotype after tissue injury is controlled by epigenetic enzymes that regulate inflammatory gene expression. We have previously identified that the histone methyltransferase SETDB2 in macrophages drives tissue repair by repressing NF-κB-mediated inflammation. Complementary ATAC-Seq and RNA-Seq of wound macrophages isolated from mice deficient in SETDB2 in myeloid cells revealed that SETDB2 suppresses the inflammatory gene program by inhibiting chromatin accessibility at NF-κB-dependent gene promoters. We found that STAT3 was required for SETDB2 expression in macrophages, yet paradoxically, it also functioned as a binding partner of SETDB2 where it repressed SETDB2 activity by inhibiting its interaction with the NF-κB component, RELA, leading to increased RELA/NF-κB-mediated inflammatory gene expression. Furthermore, RNA-Seq in wound macrophages from STAT3-deficient mice corroborated this and revealed STAT3 and SETDB2 transcriptionally coregulate overlapping genes. Finally, in diabetic wound macrophages, STAT3 expression and STAT3/SETDB2 binding were increased. We have identified what we believe to be a novel STAT3/SETDB2 axis that modulates macrophage phenotype during tissue repair and may be an important therapeutic target for nonhealing diabetic wounds.
Published: 2024
Full Text: View/download PDF

40. Diabetic Wound Keratinocytes Induce Macrophage JMJD3-Mediated Nlrp3 Expression via IL-1R Signaling.

Author: Wolf SJ, Audu CO, Moon JY, Joshi AD, Melvin WJ, Barrett EC, Mangum K, de Jimenez GS, Rocco S, Buckley S, Ahmed Z, Wasikowski R, Kahlenberg JM, Tsoi LC, Gudjonsson JE, and Gallagher KA
Subjects: Animals, Mice, Humans, Interleukin-1alpha metabolism, Interleukin-1alpha genetics, Diabetes Mellitus, Type 2 metabolism, Diabetes Mellitus, Experimental metabolism, Diabetes Mellitus, Experimental genetics, Male, Mice, Inbred C57BL, NLR Family, Pyrin Domain-Containing 3 Protein metabolism, NLR Family, Pyrin Domain-Containing 3 Protein genetics, Keratinocytes metabolism, Jumonji Domain-Containing Histone Demethylases metabolism, Jumonji Domain-Containing Histone Demethylases genetics, Macrophages metabolism, Signal Transduction physiology, Wound Healing physiology, Receptors, Interleukin-1 metabolism, Receptors, Interleukin-1 genetics, Inflammasomes metabolism
Abstract: Macrophage (Mφ) plasticity is critical for normal wound repair; however, in type 2 diabetic wounds, Mφs persist in a low-grade inflammatory state that prevents the resolution of wound inflammation. Increased NLRP3 inflammasome activity has been shown in diabetic wound Mφs; however, the molecular mechanisms regulating NLRP3 expression and activity are unclear. Here, we identified that diabetic wound keratinocytes induce Nlrp3 gene expression in wound Mφs through IL-1 receptor-mediated signaling, resulting in enhanced inflammasome activation in the presence of pathogen-associated molecular patterns and damage-associated molecular patterns. We found that IL-1α is increased in human and murine wound diabetic keratinocytes compared with nondiabetic controls and directly induces Mφ Nlrp3 expression through IL-1 receptor signaling. Mechanistically, we report that the histone demethylase, JMJD3, is increased in wound Mφs late post-injury and is induced by IL-1α from diabetic wound keratinocytes, resulting in Nlrp3 transcriptional activation through an H3K27me3-mediated mechanism. Using genetically engineered mice deficient in JMJD3 in myeloid cells (Jmjd3f/flyz2Cre+), we demonstrate that JMJD3 controls Mφ-mediated Nlrp3 expression during diabetic wound healing. Thus, our data suggest a role for keratinocyte-mediated IL-1α/IL-1R signaling in driving enhanced NLRP3 inflammasome activity in wound Mφs. These data also highlight the importance of cell cross-talk in wound tissues and identify JMJD3 and the IL-1R signaling cascade as important upstream therapeutic targets for Mφ NLRP3 inflammasome hyperactivity in nonhealing diabetic wounds., (© 2024 by the American Diabetes Association.)
Published: 2024
Full Text: View/download PDF

41. The histone methyltransferase Mixed-lineage-leukemia-1 drives T cell phenotype via Notch signaling in diabetic tissue repair.

Author: Melvin WJ, Bauer TM, Mangum KD, Audu CO, Shadiow J, Barrett EC, Joshi AD, Moon JY, Bogle R, Mazumder P, Wolf SJ, Kunke SL, Gudjonsson JE, Davis FM, and Gallagher KA
Subjects: Animals, Humans, Mice, Th17 Cells immunology, Th17 Cells metabolism, Nuclear Receptor Subfamily 1, Group F, Member 3 metabolism, Nuclear Receptor Subfamily 1, Group F, Member 3 genetics, Male, Mice, Transgenic, CD4-Positive T-Lymphocytes immunology, CD4-Positive T-Lymphocytes metabolism, Phenotype, Female, Signal Transduction, Wound Healing, Receptors, Notch metabolism, Myeloid-Lymphoid Leukemia Protein metabolism, Myeloid-Lymphoid Leukemia Protein genetics, Cell Differentiation, Histone-Lysine N-Methyltransferase metabolism, Histone-Lysine N-Methyltransferase genetics
Abstract: Immune cell-mediated inflammation is important in normal tissue regeneration but can be pathologic in diabetic wounds. Limited literature exists on the role of CD4+ T cells in normal or diabetic wound repair; however, the imbalance of CD4+ Th17/Tregs has been found to promote inflammation in other diabetic tissues. Here, using human tissue and murine transgenic models, we identified that the histone methyltransferase Mixed-lineage-leukemia-1 (MLL1) directly regulates the Th17 transcription factor RORγ via an H3K4me3 mechanism and increases expression of Notch receptors and downstream Notch signaling. Furthermore, we found that Notch receptor signaling regulates CD4+ Th cell differentiation and is critical for normal wound repair, and loss of upstream Notch pathway mediators or receptors in CD4+ T cells resulted in the loss of CD4+ Th cell differentiation in wounds. In diabetes, MLL1 and Notch-receptor signaling was upregulated in wound CD4+ Th cells, driving CD4+ T cells toward the Th17 cell phenotype. Treatment of diabetic wound CD4+ T cells with a small molecule inhibitor of MLL1 (MI-2) yielded a significant reduction in CD4+ Th17 cells and IL-17A. This is the first study to our knowledge to identify the MLL1-mediated mechanisms responsible for regulating the Th17/Treg balance in normal and diabetic wounds and to define the complex role of Notch signaling in CD4+ T cells in wounds, where increased or decreased Notch signaling both result in pathologic wound repair. Therapeutic targeting of MLL1 in diabetic CD4+ Th cells may decrease pathologic inflammation through regulation of CD4+ T cell differentiation.
Published: 2024
Full Text: View/download PDF

42. Prediagnostic Amino Acid Metabolites and Risk of Gout, Accounting for Serum Urate: Prospective Cohort Study and Mendelian Randomization.

Author: McCormick N, Joshi AD, Yokose C, Yu B, Tin A, Terkeltaub R, Merriman TR, Zeleznik O, Eliassen AH, Curhan GC, Ea HK, Nayor M, Raffield LM, and Choi HK
Abstract: Objective: Our objective was to prospectively investigate prediagnostic population-based metabolome for risk of hospitalized gout (ie, most accurate, severe, and costly cases), accounting for serum urate., Methods: We conducted prediagnostic metabolome-wide analyses among 249,677 UK Biobank participants with nuclear magnetic resonance metabolomic profiling (N = 168 metabolites, including eight amino acids) from baseline blood samples (2006-2010) without a history of gout. We calculated multivariable hazard ratios (HRs) for hospitalized incident gout, before and after adjusting for serum urate levels; we included patients with nonhospitalized incident gout in a sensitivity analysis. Potential causal effects were evaluated with two-sample Mendelian randomization., Results: Correcting for multiple testing, 107 metabolites were associated with incidence of hospitalized gout (n = 2,735) before urate adjustment, including glycine and glutamine (glutamine HR 0.64, 95% confidence interval [CI] 0.54-0.75, P = 8.3 × 10 -8 ; glycine HR 0.69, 95% CI 0.61-0.78, P = 3.3 × 10 -9 between extreme quintiles), and glycoprotein acetyls (HR 2.48, 95% CI 2.15-2.87, P = 1.96 × 10 -34 ). Associations remained significant and directionally consistent following urate adjustment (HR 0.83, 95% CI 0.70-0.98; HR 0.86, 95% CI 0.76-0.98; HR 1.41, 95% CI 1.21-1.63 between extreme quintiles), respectively; corresponding HRs per SD were 0.91 (95% CI 0.86-0.97), 0.94 (95% CI 0.91-0.98), and 1.10 (95% CI 1.06-1.14). Findings persisted when including patients with nonhospitalized incident gout. Mendelian randomization corroborated their potential causal role on hyperuricemia or gout risk; with change in urate levels of -0.05 mg/dL (95% CI -0.08 to -0.01) and -0.12 mg/dL (95% CI -0.22 to -0.03) per SD of glycine and glutamine, respectively, and odds ratios of 0.94 (95% CI 0.88-1.00) and 0.81 (95% CI 0.67-0.97) for gout., Conclusion: These prospective findings with causal implications could lead to biomarker-based risk prediction and potential supplementation-based interventions with glycine or glutamine., (© 2024 American College of Rheumatology.)
Published: 2024
Full Text: View/download PDF

43. Crosslinked-hybrid nanoparticle embedded in thermogel for sustained co-delivery to inner ear.

Author: Thakur NS, Rus I, Herbert A, Zallocchi M, Chakrabarty B, Joshi AD, Lomeo J, and Agrahari V
Subjects: Animals, Ear, Inner drug effects, Hydrogels chemistry, Cisplatin pharmacology, Cisplatin chemistry, Cell Line, Biphenyl Compounds chemistry, Drug Delivery Systems methods, Lignans chemistry, Lignans pharmacology, Lignans administration & dosage, Mice, Cell Survival drug effects, Zebrafish, Nanoparticles chemistry
Abstract: Treatment-induced ototoxicity and accompanying hearing loss are a great concern associated with chemotherapeutic or antibiotic drug regimens. Thus, prophylactic cure or early treatment is desirable by local delivery to the inner ear. In this study, we examined a novel way of intratympanically delivered sustained nanoformulation by using crosslinked hybrid nanoparticle (cHy-NPs) in a thermoresponsive hydrogel i.e. thermogel that can potentially provide a safe and effective treatment towards the treatment-induced or drug-induced ototoxicity. The prophylactic treatment of the ototoxicity can be achieved by using two therapeutic molecules, Flunarizine (FL: T-type calcium channel blocker) and Honokiol (HK: antioxidant) co-encapsulated in the same delivery system. Here we investigated, FL and HK as cytoprotective molecules against cisplatin-induced toxic effects in the House Ear Institute - Organ of Corti 1 (HEI-OC1) cells and in vivo assessments on the neuromast hair cell protection in the zebrafish lateral line. We observed that cytotoxic protective effect can be enhanced by using FL and HK in combination and developing a robust drug delivery formulation. Therefore, FL-and HK-loaded crosslinked hybrid nanoparticles (FL-cHy-NPs and HK-cHy-NPs) were synthesized using a quality-by-design approach (QbD) in which design of experiment-central composite design (DoE-CCD) following the standard least-square model was used for nanoformulation optimization. The physicochemical characterization of FL and HK loaded-NPs suggested the successful synthesis of spherical NPs with polydispersity index < 0.3, drugs encapsulation (> 75%), drugs loading (~ 10%), stability (> 2 months) in the neutral solution, and appropriate cryoprotectant selection. We assessed caspase 3/7 apopototic pathway in vitro that showed significantly reduced signals of caspase 3/7 activation after the FL-cHy-NPs and HK-cHy-NPs (alone or in combination) compared to the CisPt. The final formulation i.e. crosslinked-hybrid-nanoparticle-embedded-in-thermogel was developed by incorporating drug-loaded cHy-NPs in poloxamer-407, poloxamer-188, and carbomer-940-based hydrogel. A combination of artificial intelligence (AI)-based qualitative and quantitative image analysis determined the particle size and distribution throughout the visible segment. The developed formulation was able to release the FL and HK for at least a month. Overall, a highly stable nanoformulation was successfully developed for combating treatment-induced or drug-induced ototoxicity via local administration to the inner ear., (© 2024. The Author(s).)
Published: 2024
Full Text: View/download PDF

44. Acute Rehabilitation Experience in a Distinctive Central Nervous System Inflammatory Disorder: A Clinical Vignette.

Author: Joshi AD and Mortimer D
Subjects: Humans, Neuroinflammatory Diseases rehabilitation
Abstract: Competing Interests: Financial disclosure statements have been obtained, and no conflicts of interest have been reported by the authors or by any individuals in control of the content of this article.
Published: 2024
Full Text: View/download PDF

45. Role of Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4 Signaling in Liver and Metabolic Diseases.

Author: Ampadu F, Awasthi V, and Joshi AD
Subjects: Humans, Animals, Signal Transduction physiology, Protein Serine-Threonine Kinases metabolism, Liver metabolism, Liver enzymology, Intracellular Signaling Peptides and Proteins, Metabolic Diseases metabolism, Metabolic Diseases enzymology, Liver Diseases metabolism
Abstract: MAP4K4 is a serine/threonine protein kinase belonging to the germinal center kinase subgroup of sterile 20 protein family of kinases. MAP4K4 has been involved in regulating multiple biologic processes and a plethora of pathologies, including systemic inflammation, cardiovascular diseases, cancers, and metabolic and hepatic diseases. Recently, multiple reports have indicated the upregulation of MAP4K4 expression and signaling in hyperglycemia and liver diseases. This review provides an overview of our current knowledge of MAP4K4 structure and expression, as well as its regulation and signaling, specifically in metabolic and hepatic diseases. Reviewing these promising studies will enrich our understanding of MAP4K4 signaling pathways and, in the future, will help us design innovative therapeutic interventions against metabolic and liver diseases using MAP4K4 as a target. SIGNIFICANCE STATEMENT: Although most studies on the involvement of MAP4K4 in human pathologies are related to cancers, only recently its role in liver and other metabolic diseases is beginning to unravel. This mini review discusses recent advancements in MAP4K4 biology within the context of metabolic dysfunction and comprehensively characterizes MAP4K4 as a clinically relevant therapeutic target against liver and metabolic diseases., (Copyright © 2024 by The American Society for Pharmacology and Experimental Therapeutics.)
Published: 2024
Full Text: View/download PDF

46. Epigenetic Alteration of Smooth Muscle Cells Regulates Endothelin-Dependent Blood Pressure and Hypertensive Arterial Remodeling.

Author: Mangum KD, Li Q, Bauer TM, Wolf SJ, Shadiow J, Moon JY, Barrett EC, Joshi AD, Ahmed Z, Wasikowski R, Boyer K, Obi AT, Davis FM, Chang L, Tsoi LC, Gudjonsson J, and Gallagher KA
Abstract: Long-standing hypertension (HTN) affects multiple organ systems and leads to pathologic arterial remodeling, which is driven largely by smooth muscle cell (SMC) plasticity. Although genome wide association studies (GWAS) have identified numerous variants associated with changes in blood pressure in humans, only a small percentage of these variants actually cause HTN. In order to identify relevant genes important in SMC function in HTN, we screened three separate human GWAS and Mendelian randomization studies to identify SNPs located within non-coding gene regions, focusing on genes encoding epigenetic enzymes, as these have been recently identified to control SMC fate in cardiovascular disease. We identified SNPs rs62059712 and rs74480102 in the promoter of the human JMJD3 gene and show that the minor C allele increases JMJD3 transcription in SMCs via increased SP1 binding to the JMJD3 promoter. Using our novel SMC-specific Jmjd3-deficient murine model ( Jmjd3 flox/flox Myh11 CreERT ), we show that loss of Jmjd3 in SMCs results in HTN, mechanistically, due to decreased EDNRB expression and a compensatory increase in EDNRA expression. As a translational corollary, through single cell RNA-sequencing (scRNA-seq) of human arteries, we found strong correlation between JMJD3 and EDNRB expression in SMCs. Further, we identified that JMJD3 is required for SMC-specific gene expression, and loss of JMJD3 in SMCs in the setting of HTN results in increased arterial remodeling by promoting the SMC synthetic phenotype. Our findings link a HTN-associated human DNA variant with regulation of SMC plasticity, revealing therapeutic targets that may be used in the screening and/or personalized treatment of HTN.
Published: 2024
Full Text: View/download PDF

47. Histone demethylase JARID1C/KDM5C regulates Th17 cells by increasing IL-6 expression in diabetic plasmacytoid dendritic cells.

Author: Audu CO, Wolf SJ, Joshi AD, Moon JY, Melvin WJ, Sharma SB, Davis FM, Obi AT, Wasikowski R, Tsoi LC, Barrett EC, Mangum KD, Bauer TM, Kunkel SL, Moore BB, and Gallagher KA
Subjects: Animals, Female, Humans, Male, Mice, Interleukin-17 metabolism, Jumonji Domain-Containing Histone Demethylases metabolism, Jumonji Domain-Containing Histone Demethylases genetics, Mice, Inbred C57BL, Dendritic Cells immunology, Dendritic Cells metabolism, Interleukin-6 metabolism, Th17 Cells immunology, Th17 Cells metabolism, Wound Healing immunology
Abstract: Plasmacytoid dendritic cells (pDCs) are first responders to tissue injury, where they prime naive T cells. The role of pDCs in physiologic wound repair has been examined, but little is known about pDCs in diabetic wound tissue and their interactions with naive CD4+ T cells. Diabetic wounds are characterized by increased levels of inflammatory IL-17A cytokine, partly due to increased Th17 CD4+ cells. This increased IL-17A cytokine, in excess, impairs tissue repair. Here, using human tissue and murine wound healing models, we found that diabetic wound pDCs produced excess IL-6 and TGF-β and that these cytokines skewed naive CD4+ T cells toward a Th17 inflammatory phenotype following cutaneous injury. Further, we identified that increased IL-6 cytokine production by diabetic wound pDCs is regulated by a histone demethylase, Jumonji AT-rich interactive domain 1C histone demethylase (JARID1C). Decreased JARID1C increased IL-6 transcription in diabetic pDCs, and this process was regulated upstream by an IFN-I/TYK2/JAK1,3 signaling pathway. When inhibited in nondiabetic wound pDCs, JARID1C skewed naive CD4+ T cells toward a Th17 phenotype and increased IL-17A production. Together, this suggests that diabetic wound pDCs are epigenetically altered to increase IL-6 expression that then affects T cell phenotype. These findings identify a therapeutically manipulable pathway in diabetic wounds.
Published: 2024
Full Text: View/download PDF

48. Genome-wide interaction study of dietary intake of fibre, fruits, and vegetables with risk of colorectal cancer.

Author: Papadimitriou N, Kim A, Kawaguchi ES, Morrison J, Diez-Obrero V, Albanes D, Berndt SI, Bézieau S, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Campbell PT, Carreras-Torres R, Chan AT, Chang-Claude J, Conti DV, Devall MA, Dimou N, Drew DA, Gruber SB, Harrison TA, Hoffmeister M, Huyghe JR, Joshi AD, Keku TO, Kundaje A, Küry S, Le Marchand L, Lewinger JP, Li L, Lynch BM, Moreno V, Newton CC, Obón-Santacana M, Ose J, Pellatt AJ, Peoples AR, Platz EA, Qu C, Rennert G, Ruiz-Narvaez E, Shcherbina A, Stern MC, Su YR, Thomas DC, Thomas CE, Tian Y, Tsilidis KK, Ulrich CM, Um CY, Visvanathan K, Wang J, White E, Woods MO, Schmit SL, Macrae F, Potter JD, Hopper JL, Peters U, Murphy N, Hsu L, Gunter MJ, and Gauderman WJ
Subjects: Humans, Genotype, Diet, Male, Female, Risk Factors, Fruit, Colorectal Neoplasms genetics, Colorectal Neoplasms etiology, Dietary Fiber administration & dosage, Vegetables, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Genetic Predisposition to Disease, Gene-Environment Interaction
Abstract: Background: Consumption of fibre, fruits and vegetables have been linked with lower colorectal cancer (CRC) risk. A genome-wide gene-environment (G × E) analysis was performed to test whether genetic variants modify these associations., Methods: A pooled sample of 45 studies including up to 69,734 participants (cases: 29,896; controls: 39,838) of European ancestry were included. To identify G × E interactions, we used the traditional 1--degree-of-freedom (DF) G × E test and to improve power a 2-step procedure and a 3DF joint test that investigates the association between a genetic variant and dietary exposure, CRC risk and G × E interaction simultaneously., Findings: The 3-DF joint test revealed two significant loci with p-value <5 × 10 -8 . Rs4730274 close to the SLC26A3 gene showed an association with fibre (p-value: 2.4 × 10 -3 ) and G × fibre interaction with CRC (OR per quartile of fibre increase = 0.87, 0.80, and 0.75 for CC, TC, and TT genotype, respectively; G × E p-value: 1.8 × 10 -7 ). Rs1620977 in the NEGR1 gene showed an association with fruit intake (p-value: 1.0 × 10 -8 ) and G × fruit interaction with CRC (OR per quartile of fruit increase = 0.75, 0.65, and 0.56 for AA, AG, and GG genotype, respectively; G × E -p-value: 0.029)., Interpretation: We identified 2 loci associated with fibre and fruit intake that also modify the association of these dietary factors with CRC risk. Potential mechanisms include chronic inflammatory intestinal disorders, and gut function. However, further studies are needed for mechanistic validation and replication of findings., Funding: National Institutes of Health, National Cancer Institute. Full funding details for the individual consortia are provided in acknowledgments., Competing Interests: Declaration of interests ESK is a co-investigator in a grant from National Institutes of Health (R01CA196569). JW is Stock shareholder of Gilead Sciences Inc. AK has received consulting fees for Illumina Inc., has participated on data safety monitoring boards or advisory boards of TensorBio, PatchBio, Serimmune, and OpenTargets, and has stock or stock options of Illumina, Freenome, Deep Genomics, Immunai, TensorBio, PatchBio, and Serimmune. MCS was a co-investigator in a grant from National Institutes of Health (R01CA201407). VM has received grant support from Instituto de Salud Carlos III and Fundacion Cientifica Asociación Española Contra el Cáncer. SBG is a co-founder of Brogent international LLC. JPL has received additional grant support (5P01CA196569, 6R01CA201407). The remaining authors declare that they have no conflicts of interest., (Copyright © 2024. Published by Elsevier B.V.)
Published: 2024
Full Text: View/download PDF

49. Effect of Memantine in Chronic Poststroke Aphasia: A Clinical Vignette.

Author: Gawande SR, Joshi AD, Jhaveri RH, and Acharya A
Subjects: Humans, Chronic Disease, Excitatory Amino Acid Antagonists therapeutic use, Aphasia etiology, Aphasia drug therapy, Memantine therapeutic use, Stroke complications
Abstract: Competing Interests: Financial disclosure statements have been obtained, and no conflicts of interest have been reported by the authors or by any individuals in control of the content of this article.
Published: 2024
Full Text: View/download PDF

50. Genetic risk impacts the association of menopausal hormone therapy with colorectal cancer risk.

Author: Tian Y, Lin Y, Qu C, Arndt V, Baurley JW, Berndt SI, Bien SA, Bishop DT, Brenner H, Buchanan DD, Budiarto A, Campbell PT, Carreras-Torres R, Casey G, Chan AT, Chen R, Chen X, Conti DV, Díez-Obrero V, Dimou N, Drew DA, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gunter MJ, Harlid S, Harrison TA, Hidaka A, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl KM, Joshi AD, Keku TO, Kawaguchi E, Kim AE, Kundaje A, Larsson SC, Marchand LL, Lewinger JP, Li L, Moreno V, Morrison J, Murphy N, Nan H, Nassir R, Newcomb PA, Obón-Santacana M, Ogino S, Ose J, Pardamean B, Pellatt AJ, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez EA, Sakoda LC, Schoen RE, Shcherbina A, Stern MC, Su YR, Thibodeau SN, Thomas DC, Tsilidis KK, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, White E, Wolk A, Woods MO, Wu AH, Peters U, Gauderman WJ, Hsu L, and Chang-Claude J
Subjects: Humans, Female, Middle Aged, Case-Control Studies, Risk Factors, Aged, Hormone Replacement Therapy adverse effects, Risk Assessment, Menopause, Postmenopause, Estrogen Replacement Therapy adverse effects, Colorectal Neoplasms genetics, Colorectal Neoplasms epidemiology, Genetic Predisposition to Disease
Abstract: Background: Menopausal hormone therapy (MHT), a common treatment to relieve symptoms of menopause, is associated with a lower risk of colorectal cancer (CRC). To inform CRC risk prediction and MHT risk-benefit assessment, we aimed to evaluate the joint association of a polygenic risk score (PRS) for CRC and MHT on CRC risk., Methods: We used data from 28,486 postmenopausal women (11,519 cases and 16,967 controls) of European descent. A PRS based on 141 CRC-associated genetic variants was modeled as a categorical variable in quartiles. Multiplicative interaction between PRS and MHT use was evaluated using logistic regression. Additive interaction was measured using the relative excess risk due to interaction (RERI). 30-year cumulative risks of CRC for 50-year-old women according to MHT use and PRS were calculated., Results: The reduction in odds ratios by MHT use was larger in women within the highest quartile of PRS compared to that in women within the lowest quartile of PRS (p-value = 2.7 × 10 -8 ). At the highest quartile of PRS, the 30-year CRC risk was statistically significantly lower for women taking any MHT than for women not taking any MHT, 3.7% (3.3%-4.0%) vs 6.1% (5.7%-6.5%) (difference 2.4%, P-value = 1.83 × 10 -14 ); these differences were also statistically significant but smaller in magnitude in the lowest PRS quartile, 1.6% (1.4%-1.8%) vs 2.2% (1.9%-2.4%) (difference 0.6%, P-value = 1.01 × 10 -3 ), indicating 4 times greater reduction in absolute risk associated with any MHT use in the highest compared to the lowest quartile of genetic CRC risk., Conclusions: MHT use has a greater impact on the reduction of CRC risk for women at higher genetic risk. These findings have implications for the development of risk prediction models for CRC and potentially for the consideration of genetic information in the risk-benefit assessment of MHT use., (© 2024. The Author(s).)
Published: 2024
Full Text: View/download PDF

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Topic

Publication Year Range

Language

Publication Type

Journal

Region

Database

Publisher

318 results on '"Joshi AD"'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources