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We tested the causality between education and smoking using the natural experiment of discordant twin pairs allowing to optimally control for background genetic and childhood social factors. Data from 18 cohorts including 10,527 monozygotic (MZ) and same-sex dizygotic (DZ) twin pairs discordant for education and smoking were analyzed by linear fixed effects regression models. Within twin pairs, education levels were lower among the currently smoking than among the never smoking co-twins and this education difference was larger within DZ than MZ pairs. Similarly, education levels were higher among former smoking than among currently smoking co-twins, and this difference was larger within DZ pairs. Our results support the hypothesis of a causal effect of education on both current smoking status and smoking cessation. However, the even greater intra-pair differences within DZ pairs, who share only 50% of their segregating genes, provide evidence that shared genetic factors also contribute to these associations.

To investigate the correlation between serum level of homocysteine (Hcy) and ulcerative colitis (UC) and evaluate its diagnostic performance by pooling the open published data.

Simple Summary: Pituitary adenomas often regrow after surgery, posing a treatment challenge. By studying the DNA methylation patterns of these adenomas, we aimed to identify different subtypes that may predict regrowth potential. Samples from 33 patients with nonfunctioning pituitary adenomas were analyzed, revealing distinct DNA methylation clusters. While trends suggesting certain clusters might be associated with higher regrowth potential emerged, overall significant differences in regrowth rates between these clusters were not found. DNA methylation profiling could help identify adenomas prone to regrowth, potentially improving treatment strategies in the future. Further larger studies are needed to confirm the findings from this explorative pilot study. Background: The prediction of the regrowth potential of pituitary adenomas after surgery is challenging. The genome-wide DNA methylation profiling of pituitary adenomas may separate adenomas into distinct methylation classes corresponding to histology-based subtypes. Specific genes and differentially methylated probes involving regrowth have been proposed, but no study has linked this epigenetic variance with regrowth potential and the clinical heterogeneity of nonfunctioning pituitary adenomas. This study aimed to investigate whether DNA methylation profiling can be useful as a clinical prognostic marker. Methods: A DNA methylation analysis by Illumina's MethylationEPIC array was performed on 54 pituitary macroadenomas from patients who underwent transsphenoidal surgery during 2007–2017. Twelve patients were excluded due to an incomplete postoperative follow-up, degenerated biobank-stored tissue, or low DNA methylation quality. For the quantitative measurement of the tumor regrowth rate, we conducted a 3D volumetric analysis of tumor remnant volume via annual magnetic resonance imaging. A linear mixed effects model was used to examine whether different DNA methylation clusters had different regrowth patterns. Results: The DNA methylation profiling of 42 tissue samples showed robust DNA methylation clusters, comparable with previous findings. The subgroup of 33 nonfunctioning pituitary adenomas of an SF1-lineage showed five subclusters with an approximately unbiased score of 86%. There were no overall statistically significant differences when comparing hazard ratios for regrowth of 100%, 50%, or 0%. Despite this, plots of correlated survival estimates suggested higher regrowth rates for some clusters. The mixed effects model of accumulated regrowth similarly showed tendencies toward an association between specific DNA methylation clusters and regrowth potential. Conclusion: The DNA methylation profiling of nonfunctioning pituitary adenomas may potentially identify adenomas with increased growth and recurrence potential. Larger validation studies are needed to confirm the findings from this explorative pilot study. [ABSTRACT FROM AUTHOR]

Background & aimsWe analyzed data from twins to determine how much the familial risk of colorectal cancer can be attributed to genetic factors vs environment. We also examined whether heritability is distinct for colon vs rectal cancer, given evidence of distinct etiologies.MethodsOur data set included 39,990 monozygotic and 61,443 same-sex dizygotic twins from the Nordic Twin Study of Cancer. We compared each cancer's risk in twins of affected co-twins relative to the cohort risk (familial risk ratio [FRR]). We then estimated the proportion of variation in risk that could be attributed to genetic factors (heritability).ResultsFrom earliest registration in 1943 through 2010, there were 1861 individuals diagnosed with colon cancer and 1268 diagnosed with rectal cancer. Monozygotic twins of affected co-twins had an FRR for colorectal cancer of 3.1 (95% confidence interval [CI], 2.4-3.8) relative to the cohort risk. Dizygotic twins of affected co-twins had an FRR for colorectal cancer of 2.2 (95% CI, 1.7-2.7). We estimated that 40% (95% CI, 33%-48%) of the variation in colorectal cancer risk could be attributed to genetic factors; unique environment only accounted for the remaining liability. For colon cancer, the FRR was 3.3 (95% CI, 2.1-4.5) for monozygotic twins and 2.6 (95% CI, 1.7-3.5) for dizygotic twins. For rectal cancer, comparable estimates were 3.3 (95% CI, 1.5-5.1) for monozygotic twins and 2.6 (95% CI, 1.2-4.0) for dizygotic twins. Heritability estimates for colon and rectal cancer were 16% (95% CI, 0-46%) and 15% (95% CI, 0-50%), common environment estimates were 15% (95% CI, 0-38%) and 11% (95% CI, 0-38%), and unique environment estimates were 68% (95% CI, 57%-79%) and 75% (95% CI, 61%-88%), respectively.ConclusionsInterindividual genetic differences could account for 40% of the variation in susceptibility to colorectal cancer; risk for colon and rectal cancers might have less of a genetic component than risk for colorectal cancer. Siblings, and particularly monozygotic co-twins, of individuals with colon or rectal cancer should consider personalized screening.

Background: Current clinical markers overestimate the recurrence risk in many lymph node negative (LNN) breast cancer (BC) patients such that a majority of these low‐risk patients unnecessarily receive systemic treatments. We tested if differential microRNA expression in primary tumors allows reliable identification of indolent LNN BC patients to provide an improved classification tool for overtreatment reduction in this patient group. Methods: We collected freshly frozen primary tumors of 80 LNN BC patients with recurrence and 80 recurrence‐free patients (mean follow‐up: 20.9 years). The study comprises solely systemically untreated patients to exclude that administered treatments confound the metastasis status. Samples were pairwise matched for clinical‐pathological characteristics to minimize dependence of current markers. Patients were classified into risk‐subgroups according to the differential microRNA expression of their tumors via classification model building with cross‐validation using seven classification methods and a voting scheme. The methodology was validated using available data of two independent cohorts (n = 123, n = 339). Results: Of the 80 indolent patients (who would all likely receive systemic treatments today) our ultralow‐risk classifier correctly identified 37 while keeping a sensitivity of 100% in the recurrence group. Multivariable logistic regression analysis confirmed independence of voting results from current clinical markers. Application of the method in two validation cohorts confirmed successful classification of ultralow‐risk BC patients with significantly prolonged recurrence‐free survival. Conclusion: Profiles of differential microRNAs expression can identify LNN BC patients who could spare systemic treatments demanded by currently applied classifications. However, further validation studies are required for clinical implementation of the applied methodology. Our study shows that differential microRNA expression analysis has the potential to identify a subgroup of Breast cancer (BC) patients with an extremely low long‐term risk of metastases. The ensemble‐based classification approach developed could form the starting point for a diagnostic tool to avoid unnecessary overtreatment of a significant proportion of BC patients. [ABSTRACT FROM AUTHOR]

Abstract Background Existing literature indicates that ADRB2 gene is associated with health and longevity, but none of previous studies investigated associations of carrying the ADRB2 minor alleles and interactions between ADRB2 genotypes and social/behavioral factors(GxE) with health outcomes at advanced ages. This study intends to fill in this research gap. Method We conducted an exploratory analysis, using longitudinal survey phenotype/genotype data from 877 oldest-old aged 90+. To estimate association of GxE interactions with health outcome, adjusted for the potential correlation between genotypes and social/behavioral factors and various other potentially confounding factors, we develop and test an innovative three-step procedure which combines logistic regression and structural equation methods. Results Interaction between regular exercise and carrying rs1042718 minor allele is significantly and positively associated with good cognitive function; interaction between regular exercise and carrying rs1042718 or rs1042719 minor allele is significantly and positively associated with self-reported good health; and interaction between social-leisure activities and carrying rs1042719 minor allele is significantly and positively associated with self-reported good health. Carrying rs1042718 or rs1042719 minor alleles is significantly and negatively associated with negative emotion, but the ADRB2 SNPs are not significantly associated with cognitive function and self-reported health. Our structural equation analysis found that, adjusted for the confounding effects of correlation of the ADRB2 SNPs with negative emotion, interaction between negative emotion and carrying rs1042718 or rs1042719 minor allele is significantly and negatively associated with cognitive function. The positive association of regular exercise and social-leisure activities with cognitive function and self-reported health, and negative association of negative emotion with cognitive function, were much stronger among carriers of rs1042718 or rs1042719 alleles, compared to the non-carriers. Conclusions The results indicate significant positive associations of interactions between social/behavioral factors and the ADRB2 genotypes with health outcomes of cognitive function and self-reported health, and negative associations of carrying rs1042718 or rs1042719 minor alleles with negative emotion, at advanced ages in China. Our findings are exploratory rather than causal conclusions. This study implies that near-future health promotion programs considering individuals’ genetic profiles, with appropriate protection of privacy/confidentiality, would yield increased benefits and reduced costs to the programs and their participants.

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.