Preparing ESL Students for Job Interviews
In this insightful content, discover the special reasons ESL students feel anxious about job interviews and the fears they express. Learn keys to help students succeed, including changing their mindset, building self-confidence, and effective interview preparation techniques.
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Journal club Sept 16, 2019 EWAS 7 DNAm score 1 Method 2 Mechanism 1 Review 1
EWAS (longitudinal) Body Mass Index Drives Changes in DNA Methylation: A Longitudinal Study. Body Mass Index Drives Changes in DNA Methylation: A Longitudinal Study. Sun D, Zhang T, Su S, Hao G, Chen T, Li QZ, Bazzano LA, He J, Wang X, Li S, Chen W. Sun D, Zhang T, Su S, Hao G, Chen T, Li QZ, Bazzano LA, He J, Wang X, Li S, Chen W. Circ Res. 2019 Sep 12. Circ Res. 2019 Sep 12. n=995 White and n=490 Black from the Bogalusa Heart Study DNAm and BMI measured 6.2 years apart in 439 white and 201 Black Replication in 252 White and 228 Black from the Georgia Stress and Heart Study 349 CpG sites (266 novel) in Whites and 36 (21 novel) in Blacks with replicated associations with BMI 8 sites in common cross-lagged panel analyses identified paths from BMI to DNAm but not the opposite.
EWAS (longitudinal) Socioeconomic status and DNA methylation from birth through mid Socioeconomic status and DNA methylation from birth through mid- -childhood: a prospective study in Project Viva. Project Viva. Laubach ZM, Perng W, Cardenas A, Rifas Laubach ZM, Perng W, Cardenas A, Rifas- -Shiman SL, Oken E, DeMeo D, Litonjua AA, Duca RC, Godderis Shiman SL, Oken E, DeMeo D, Litonjua AA, Duca RC, Godderis L, Baccarelli A, Hivert MF. L, Baccarelli A, Hivert MF. Epigenomics. 2019 Sep 11. Epigenomics. 2019 Sep 11. DNAm for 609 children at birth (cord), age 3 and age 7 (peripheral blood) in Project VIVA. Differences were tested between the top and bottom 10% of SES (not sure if this means n=60 vs 60) 4 differences observed in cord and 1 persisted beyond birth. childhood: a prospective study in
EWAS (case-control) Epigenome Epigenome- -Wide Association Study of Incident Type 2 Diabetes in a British Population: EPIC Wide Association Study of Incident Type 2 Diabetes in a British Population: EPIC- -Norfolk Study. Cardona A, Day FR, Perry JRB, Loh M, Chu AY, Lehne B, Paul DS, Lotta LA, Stewart ID, Kerrison ND, Scott RA, Cardona A, Day FR, Perry JRB, Loh M, Chu AY, Lehne B, Paul DS, Lotta LA, Stewart ID, Kerrison ND, Scott RA, Khaw KT, Forouhi NG, Langenberg C, Liu C, Mendelson MM, Levy D, Beck S, Leslie RD, Dupuis J, Meigs JB, Khaw KT, Forouhi NG, Langenberg C, Liu C, Mendelson MM, Levy D, Beck S, Leslie RD, Dupuis J, Meigs JB, Kooner JS, Pihlajam ki J, Vaag A, Perfilyev A, Ling C, Hivert MF, Chambers JC, Wareham NJ, Ong KK. Kooner JS, Pihlajam ki J, Vaag A, Perfilyev A, Ling C, Hivert MF, Chambers JC, Wareham NJ, Ong KK. Diabetes. 2019 Sep 10. Diabetes. 2019 Sep 10. Case-control study of T2DM DNAm measured in blood collected 'before onset' (up to 11 years) 18 differentially methylated CpG sites, 3 observed previously 16 had meQTLs, one indicated a causal role for DNAm Norfolk Study.
EWAS (predictive) A methylation study of long A methylation study of long- -term depression risk. Clark SL, Hattab MW, Chan RF, Shabalin AA, Han LKM, Zhao M, Smit JH, Jansen R, Milaneschi Y, Xie LY, Clark SL, Hattab MW, Chan RF, Shabalin AA, Han LKM, Zhao M, Smit JH, Jansen R, Milaneschi Y, Xie LY, van Grootheest G, Penninx BWJH, Aberg KA, van den Oord EJCG. van Grootheest G, Penninx BWJH, Aberg KA, van den Oord EJCG. Mol Psychiatry. 2019 Sep 9. Mol Psychiatry. 2019 Sep 9. term depression risk. "blood DNA methylation profiles from 581 MDD patients at baseline with MDD status 6 years later" DNA methylation by MBD-seq "A resampling approach showed a highly significant association between methylation profiles in blood at baseline and future disease status (P = 2.0 10-16)." DNA methylation risk score had AUC=0.724, better than genetic or clinical predictors.
EWAS (twins) Peripheral blood DNA methylation differences in twin pairs discordant for Alzheimer's disease. Peripheral blood DNA methylation differences in twin pairs discordant for Alzheimer's disease. Konki M, Malonzo M, Karlsson IK, Lindgren N, Ghimire B, Smolander J, Scheinin NM, Ollikainen M, Laiho Konki M, Malonzo M, Karlsson IK, Lindgren N, Ghimire B, Smolander J, Scheinin NM, Ollikainen M, Laiho A, Elo LL, L nnberg T, R ytt M, Pedersen NL, Kaprio J, L hdesm ki H, Rinne JO, Lund RJ. A, Elo LL, L nnberg T, R ytt M, Pedersen NL, Kaprio J, L hdesm ki H, Rinne JO, Lund RJ. Clin Epigenetics. 2019 Sep 2;11(1):130. Clin Epigenetics. 2019 Sep 2;11(1):130. 23 disease discordant twin pairs blood methylation profiles 11 genomic regions with >15% methylation differences Selected one region for replication follow-up in 120 twin pairs indicates that effect in that region caused by the disease state
EWAS The effect of age on DNA methylation in whole blood among Bangladeshi men and women. The effect of age on DNA methylation in whole blood among Bangladeshi men and women. Jansen RJ, Tong L, Argos M, Jasmine F, Rakibuz Jansen RJ, Tong L, Argos M, Jasmine F, Rakibuz- -Zaman M, Sarwar G, Islam MT, Shahriar H, Islam T, Zaman M, Sarwar G, Islam MT, Shahriar H, Islam T, Rahman M, Yunus M, Kibriya MG, Baron JA, Ahsan H, Pierce BL. Rahman M, Yunus M, Kibriya MG, Baron JA, Ahsan H, Pierce BL. BMC Genomics. 2019 Sep 10;20(1):704. BMC Genomics. 2019 Sep 10;20(1):704. blood for 400 adult participants (189 males and 211 females) from Bangladesh age range 25-70 986 CpG sites associated with age among men 3479 among women over 60% replicated resulting age predictor had R=0.8 correlation with chronological age ...
EWAS Placental DNA Methylation Mediates the Association of Prenatal Maternal Smoking on Birth Weight. Placental DNA Methylation Mediates the Association of Prenatal Maternal Smoking on Birth Weight. Cardenas A, Lutz SM, Everson TM, Perron P, Bouchard L, Hivert MF. Cardenas A, Lutz SM, Everson TM, Perron P, Bouchard L, Hivert MF. Am J Epidemiol. 2019 Sep 9. pii: kwz184. Am J Epidemiol. 2019 Sep 9. pii: kwz184. n=441 placentas 71 CpG sites associated with prenatal smoking 7 found to mediate effect (50-87% of 175g effect)
DNAm score Validated inference of smoking habits from blood with a finite DNA methylation marker set. Validated inference of smoking habits from blood with a finite DNA methylation marker set. Maas SCE, Vidaki A, Wilson R, Teumer A, Liu F, van Meurs JBJ, Uitterlinden AG, Boomsma DI, de Geus EJC, Maas SCE, Vidaki A, Wilson R, Teumer A, Liu F, van Meurs JBJ, Uitterlinden AG, Boomsma DI, de Geus EJC, Willemsen G, van Dongen J, van der Kallen CJH, Slagboom PE, Beekman M, van Heemst D, van den Berg LH; Willemsen G, van Dongen J, van der Kallen CJH, Slagboom PE, Beekman M, van Heemst D, van den Berg LH; BIOS Consortium, Duijts L, Jaddoe VWV, Ladwig KH, Kunze S, Peters A, Ikram MA, Grabe HJ, Felix JF, BIOS Consortium, Duijts L, Jaddoe VWV, Ladwig KH, Kunze S, Peters A, Ikram MA, Grabe HJ, Felix JF, Waldenberger M, Franco OH, Ghanbari M, Kayser M. Waldenberger M, Franco OH, Ghanbari M, Kayser M. Eur J Epidemiol. 2019 Sep 7. Eur J Epidemiol. 2019 Sep 7. 14 epigenome-wide association studies for marker discovery 6 population-based cohorts (N = 3764) for model building 13-CpG signature Area Under the Curve (AUC)=0.9 for differentiating current vs never AUC=0.7 for former AUC=0.78 for never AUC=0.8 for >10 pack-year smokers Children age 6 found to be non-smokers even with prenatal smoking exposure.
Method Methods for Dealing With Missing Covariate Data in Epigenome Methods for Dealing With Missing Covariate Data in Epigenome- -Wide Association Studies. Mills HL, Heron J, Relton C, Suderman M, Tilling K. Mills HL, Heron J, Relton C, Suderman M, Tilling K. Am J Epidemiol. 2019 Sep 5. pii: kwz186. Am J Epidemiol. 2019 Sep 5. pii: kwz186. Wide Association Studies. Proposes and evaluates several adaptations of multiple imputation for EWAS The fastest are biased but some 'reasonably' fast approaches are not
Method TOAST: improving reference TOAST: improving reference- -free cell composition estimation by cross free cell composition estimation by cross- -cell type differential analysis. Li Z, Wu H. Li Z, Wu H. Genome Biol. 2019 Sep 4;20(1):190. Genome Biol. 2019 Sep 4;20(1):190. cell type differential analysis. Reference-free methods highly dependent on the set of CpG sites selected to estimate cell counts. Most methods essentially end up selecting the most variable sites. Algorithm iterates between: Applying reference-free method Identifying cell-type discordant CpG sites Show that this algorithm improves performance
Mechanism The histone mark H3K36me2 recruits DNMT3A and shapes the intergenic DNA methylation landscape. The histone mark H3K36me2 recruits DNMT3A and shapes the intergenic DNA methylation landscape. Weinberg DN, Papillon Weinberg DN, Papillon- -Cavanagh S, Chen H, Yue Y, Chen X, Rajagopalan KN, Horth C, McGuire JT, Xu X, Cavanagh S, Chen H, Yue Y, Chen X, Rajagopalan KN, Horth C, McGuire JT, Xu X, Nikbakht H, Lemiesz AE, Marchione DM, Marunde MR, Meiners MJ, Cheek MA, Keogh MC, Bareke E, Djedid Nikbakht H, Lemiesz AE, Marchione DM, Marunde MR, Meiners MJ, Cheek MA, Keogh MC, Bareke E, Djedid A, Harutyunyan AS, Jabado N, Garcia BA, Li H, Allis CD, Majewski J, Lu C. A, Harutyunyan AS, Jabado N, Garcia BA, Li H, Allis CD, Majewski J, Lu C. Nature. 2019 Sep;573(7773):281 Nature. 2019 Sep;573(7773):281- -286. 286. "NSD1-mediated H3K36me2 is required for the recruitment of DNMT3A and maintenance of DNA methylation at intergenic regions."
Review The NIH Common Fund/Roadmap Epigenomics Program: Successes of a comprehensive consortium. The NIH Common Fund/Roadmap Epigenomics Program: Successes of a comprehensive consortium. Satterlee JS, Chadwick LH, Tyson FL, McAllister K, Beaver J, Birnbaum L, Volkow ND, Wilder EL, Satterlee JS, Chadwick LH, Tyson FL, McAllister K, Beaver J, Birnbaum L, Volkow ND, Wilder EL, Anderson JM, Roy AL. Anderson JM, Roy AL. Sci Adv. 2019 Jul 10;5(7):eaaw6507 Sci Adv. 2019 Jul 10;5(7):eaaw6507 Highlights 1) Critical analysis of current funding reveals gaps where Common Fund support can have the greatest impact; 2) Scientific gaps often occur around issues that cannot be addressed by a single researcher and that require a multidisciplinary and coordinated effort to achieve; 3) Development of community resources requires consistent input from scientists who represent the user community; 4) Community resources need to be developed in the context of the international community this requires dedicated time and effort; 5) Principal investigators funded to generate a community resource need to commit to consortium goals and community outreach; 6) Early sharing of large datasets and tools does not impede the work of data/tool generators it enhances the impact of the data/tools 7) The combination of consortium-driven community resource development in addition to discovery and technology development projects can result in rapid advances for the field as a whole.
