Perheittäin esiintyvän paksusuolisyövän ja kohdun runko-osan syövän molekyyligeneettinen luokittelu

Hereditary nonpolyposis colorectal cancer (HNPCC) is the most common known clearly hereditary cause of colorectal and endometrial cancer (CRC and EC). Dominantly inherited mutations in one of the known mismatch repair (MMR) genes predispose to HNPCC. Defective MMR leads to an accumulation of mutations especially in repeat tracts, presenting microsatellite instability. HNPCC is clinically a very heterogeneous disease. The age at onset varies and the target tissue may vary. In addition, families that fulfill the diagnostic criteria for HNPCC but fail to show any predisposing mutation in MMR genes exist. Our aim was to evaluate the genetic background of familial CRC and EC. We performed comprehensive molecular and DNA copy number analyses of CRCs fulfilling the diagnostic criteria for HNPCC. We studied the role of five pathways (MMR, Wnt, p53, CIN, PI3K/AKT) and divided the tumors into two groups, one with MMR gene germline mutations and the other without. We observed that MMR proficient familial CRC consist of two molecularly distinct groups that differ from MMR deficient tumors. Group A shows paucity of common molecular and chromosomal alterations characteristic of colorectal carcinogenesis. Group B shows molecular features similar to classical microsatellite stable tumors with gross chromosomal alterations. Our finding of a unique tumor profile in group A suggests the involvement of novel predisposing genes and pathways in colorectal cancer cohorts not linked to MMR gene defects. We investigated the genetic background of familial ECs. Among 22 families with clustering of EC, two (9%) were due to MMR gene germline mutations. The remaining familial site-specific ECs are largely comparable with HNPCC associated ECs, the main difference between these groups being MMR proficiency vs. deficiency. We studied the role of PI3K/AKT pathway in familial ECs as well and observed that PIK3CA amplifications are characteristic of familial site-specific EC without MMR gene germline mutations. Most of the high-level amplifications occurred in tumors with stable microsatellites, suggesting that these tumors are more likely associated with chromosomal rather than microsatellite instability and MMR defect. The existence of site-specific endometrial carcinoma as a separate entity remains equivocal until predisposing genes are identified. It is possible that no single highly penetrant gene for this proposed syndrome exists, it may, for example be due to a combination of multiple low penetrance genes. Despite advances in deciphering the molecular genetic background of HNPCC, it is poorly understood why certain organs are more susceptible than others to cancer development. We found that important determinants of the HNPCC tumor spectrum are, in addition to different predisposing germline mutations, organ specific target genes and different instability profiles, loss of heterozygosity at MLH1 locus, and MLH1 promoter methylation. This study provided more precise molecular classification of families with CRC and EC. Our observations on familial CRC and EC are likely to have broader significance that extends to sporadic CRC and EC as well.Kohdun runko-osan syöpä ja paksusuolisyöpä kuuluvat kolmen yleisimmän syöpätaudin joukkoon länsimaissa. Selvästi periytyvistä muodoista yleisin on periytyvä ei-polypoottinen paksusuolisyöpäsyndrooma (hereditary nonpolyposis colorectal cancer, HNPCC), joka aiheuttaa noin 1-5 % kaikista paksusuolen ja kohdun runko-osan syövistä. HNPCC periytyy vallitsevasti ja sille altistavat DNA:ta korjaavien mismatch repair (MMR) geenien (MLH1, MSH2, MSH3, MSH6 ja PMS2) mutaatiot. MMR geenien mutaatiot aiheuttavat korjausmekanismin puutteellisen toiminnan ja virheiden kertymisen solun DNA:han. Tämän tutkimuksen tarkoituksena oli selvittää suvuittain esiintyvän paksusuolisyövän ja kohdun runko-osan syövän geneettistä taustaa. Teimme kattavat molekyyligeneettiset ja kopiolukuihin perustuvat analyysit tutkimalla HNPCC -kriteerit täyttäviä paksusuolisyöpiä. Merkittävin löydöksemme oli niiden syöpien, joiden taustalta ei löytynyt MMR geenien ituratamutaatiota, jakautuminen kahteen ryhmään. Ryhmä A koostuu syövistä, joista ei löydy paksusuolisyövälle tunnusomaisia molekyyli- eikä kromosomitason muutoksia. Ryhmä B puolestaan edustaa klassista paksusuolisyöpäpopulaatiota, jolle stabiilit mikrosatelliitit sekä runsaat kromosomitason muutokset ovat tyypillisiä. Tutkimustemme mukaan ryhmä A on ainutlaatuinen joukko paksusuolisyöpiä, joiden taustalla on todennäköisesti vielä tuntemattomia sairaudelle altistavia geenejä ja signaalireittejä. Selvitimme suvuittain esiintyvän kohdun runko-osan syövän geneettistä taustaa tutkimalla MMR geenien ja PI3K/AKT signaalireitin osuutta näiden syöpien kehittymisessä. Yhteensä 9 %:ssa perheistä, joissa esiintyy sattumaa useammin kohdun runko-osan syöpää, löytyi ituratamutaatio MMR geenistä. Nämä perheet edustavat epätyypillistä HNPCC syndroomaa, joka ilmentyy kohdun runko-osan syöpänä ilman syndroomalle tyypillisiä paksusuolen syöpäkasvaimia. Suurimmassa osassa (91%) perheitä ei löytynyt periytyvää MMR geenin mutaatiota. Näissä perheissä kromosomaaliset muutokset, pikemmin kuin MMR mekanismin toimimattomuus, ovat osallisena kohdun runko-osan syöpien kehittymiseen. Tutkimuksemme jälkeen jäi vielä epäselväksi muodostavatko kyseiset perheet itsenäisen kokonaisuuden, jonka taustalla on yhden geenin virhe, vai ovatko sattumaa useammin esiintyvät kohdun runko-osan syövät näissä perheissä usean eri geenin sekä ympäristön yhteisvaikutuksen tulos. HNPCC -syndrooman geneettinen tausta tunnetaan hyvin, mutta on yhä epäselvää miksi juuri tietyt kudokset ovat erityisen alttiita kasvainten kehittymiselle. Erilaisilla ituratamutaatioilla ja kudosspesifeillä kohdegeeneillä on vaikutuksensa eri kudosten syöpäalttiuteen. Havaitsimme, että HNPCC syöpäkirjon määräytymiseen vaikuttavat lisäksi MLH1 -geenipaikan häviäminen sekä MLH1 -geenin hypermetylaatio. Tässä tutkimuksessa suvuittain esiintyvät paksusuolen syövät ja kohdun runko-osan syövät luokiteltiin tarkemmin molekyyligenetiikan keinoin. Havainnoistamme on todennäköisesti hyötyä myös satunnaisesti esiintyvien syöpien luokittelulle ja sitä kautta mahdollisesti tulevaisuudessa myös potilaiden yksilöidyn hoidon suunnittelulle

The potential of DNA methylation as a biomarker for obesity and smoking

Peer reviewe

Mendelian randomization in (epi)genetic epidemiology : an effective tool to be handled with care

A study examining blood lipid traits takes epigenomics approaches to the next level by using carefully performed Mendelian randomization to assess causality rather than simply reporting associations.Non peer reviewe

Making Sense of the Epigenome Using Data Integration Approaches

Epigenetic research involves examining the mitotically heritable processes that regulate gene expression, independent of changes in the DNA sequence. Recent technical advances such as whole-genome bisulfite sequencing and affordable epigenomic array-based technologies, allow researchers to measure epigenetic profiles of large cohorts at a genome-wide level, generating comprehensive high-dimensional datasets that may contain important information for disease development and treatment opportunities. The epigenomic profile for a certain disease is often a result of the complex interplay between multiple genetic and environmental factors, which poses an enormous challenge to visualize and interpret these data. Furthermore, due to the dynamic nature of the epigenome, it is critical to determine causal relationships from the many correlated associations. In this review we provide an overview of recent data analysis approaches to integrate various omics layers to understand epigenetic mechanisms of complex diseases, such as obesity and cancer. We discuss the following topics: (i) advantages and limitations of major epigenetic profiling techniques, (ii) resources for standardization, annotation and harmonization of epigenetic data, and (iii) statistical methods and machine learning methods for establishing data-driven hypotheses of key regulatory mechanisms. Finally, we discuss the future directions for data integration that shall facilitate the discovery of epigenetic-based biomarkers and therapies

Differences in DNA Methylation-Based Age Prediction Within Twin Pairs Discordant for Cancer

DNA methylation-based age acceleration (DNAmAA) is associated with cancer, with both cancer tissue and blood showing increased DNAmAA. We aimed to investigate whether DNAmAA is associated with cancer risk within twin pairs discordant for cancer, and whether DNAmAA has the potential to serve as a biomarker for such. The study included 47 monozygotic and 48 same-sex-dizygotic cancer-discordant twin pairs from the Finnish Twin Cohort study with blood samples available between 17 and 31 years after the cancer diagnosis. We studied all cancers (95 pairs), then separately breast cancer (24 pairs) and all sites other than breast cancer (71 pairs). DNAmAA was calculated for seven models: Horvath, Horvath intrinsic epigenetic age acceleration, Hannum, Hannum intrinsic epigenetic age acceleration, Hannum extrinsic epigenetic age acceleration, PhenoAge and GrimAge. Within-pair differences in DNAmAA were analyzed by paired t tests and linear regression. Twin pairs sampled before cancer diagnosis did not differ significantly in DNAmAA. However, the within-pair differences in DNAmAA before cancer diagnosis increased significantly the closer the cancer diagnosis was, and this acceleration extended for years after the diagnosis. Pairs sampled after the diagnosis differed for DNAmAA with the Horvath models capturing cancer diagnosis-associated DNAmAA across all three cancer groupings. The results suggest that DNAmAA in blood is associated with cancer diagnosis. This may be due to epigenetic alterations in relation to cancer, its treatment or associated lifestyle changes. Based on the current study, the biomarker potential of DNAmAA in blood appears to be limited.Peer reviewe

The role of adolescent lifestyle habits in biological aging : A prospective twin study

Background: Adolescence is a stage of fast growth and development. Exposures during puberty can have long -term effects on health in later life. This study aims to investigate the role of adolescent lifestyle in biological aging. Methods: The study participants originated from the longitudinal FinnTwin12 study (n = 5114). Adolescent lifestyle-related factors, including body mass index (BMI), leisure -time physical activity, smoking, and alcohol use, were based on self-reports and measured at ages 12, 14, and 17 years. For a subsample, blood -based DNA methylation (DNAm) was used to assess biological aging with six epigenetic aging measures in young adulthood (21-25 years, n = 824). A latent class analysis was conducted to identify patterns of lifestyle behaviors in adolescence, and differences between the subgroups in later biological aging were studied. Genetic and environmental influences on biological aging shared with lifestyle behavior patterns were estimated using quantitative genetic modeling. Results: We identified five subgroups of participants with different adolescent lifestyle behavior patterns. When DNAm GrimAge, DunedinPoAm, and DunedinPACE estimators were used, the class with the unhealthiest lifestyle and the class of participants with high BMI were biologically older than the classes with healthier lifestyle habits. The differences in lifestyle-related factors were maintained into young adulthood. Most of the variation in biological aging shared with adolescent lifestyle was explained by common genetic factors. Conclusions: These findings suggest that an unhealthy lifestyle during pubertal years is associated with accelerated biological aging in young adulthood. Genetic pleiotropy may largely explain the observed associations.Peer reviewe

Pre-diagnosis blood DNA methylation profiling of twin pairs discordant for breast cancer points to the importance of environmental risk factors

Background: Assessment of breast cancer (BC) risk generally relies on mammography, family history, reproductive history, and genotyping of major mutations. However, assessing the impact of environmental factors, such as lifestyle, health-related behavior, or external exposures, is still challenging. DNA methylation (DNAm), capturing both genetic and environmental effects, presents a promising opportunity. Previous studies have identified associations and predicted the risk of BC using DNAm in blood; however, these studies did not distinguish between genetic and environmental contributions to these DNAm sites. In this study, associations between DNAm and BC are assessed using paired twin models, which control for shared genetic and environmental effects, allowing testing for associations between DNAm and non-shared environmental exposures and behavior. Results: Pre-diagnosis blood samples of 32 monozygotic (MZ) and 76 dizygotic (DZ) female twin pairs discordant for BC were collected at the mean age of 56.0 years, with the mean age at diagnosis 66.8 years and censoring 75.2 years. We identified 212 CpGs (p &lt; 6.4*10–8) and 15 DMRs associated with BC risk across all pairs using paired Cox proportional hazard models. All but one of the BC risks associated with CpGs were hypomethylated, and 198/212 CpGs had their DNAm associated with BC risk independent of genetic effects. According to previous literature, at least five of the top CpGs were related to estrogen signaling. Following a comprehensive two-sample Mendelian randomization analysis, we found evidence supporting a dual causal impact of DNAm at cg20145695 (gene body of NXN, rs480351) with increased risk for estrogen receptor positive BC and decreased risk for estrogen receptor negative BC. Conclusion: While causal effects of DNAm on BC risk are rare, most of the identified CpGs associated with the risk of BC appear to be independent of genetic effects. This suggests that DNAm could serve as a valuable biomarker for environmental risk factors for BC, and may offer potential benefits as a complementary tool to current risk assessment procedures.</p

Neonatal DNA methylation profile in human twins is specified by a complex interplay between intrauterine environmental and genetic factors, subject to tissue-specific influence

Comparison between groups of monozygotic (MZ) and dizygotic (DZ) twins enables an estimation of the relative contribution of genetic and shared and nonshared environmental factors to phenotypic variability. Using DNA methylation profiling of ∼20,000 CpG sites as a phenotype, we have examined discordance levels in three neonatal tissues from 22 MZ and 12 DZ twin pairs. MZ twins exhibit a wide range of within-pair differences at birth, but show discordance levels generally lower than DZ pairs. Within-pair methylation discordance was lowest in CpG islands in all twins and increased as a function of distance from islands. Variance component decomposition analysis of DNA methylation in MZ and DZ pairs revealed a low mean heritability across all tissues, although a wide range of heritabilities was detected for specific genomic CpG sites. The largest component of variation was attributed to the combined effects of nonshared intrauterine environment and stochastic factors. Regression analysis of methylation on birth weight revealed a general association between methylation of genes involved in metabolism and biosynthesis, providing further support for epigenetic change in the previously described link between low birth weight and increasing risk for cardiovascular, metabolic, and other complex diseases. Finally, comparison of our data with that of several older twins revealed little evidence for genome-wide epigenetic drift with increasing age. This is the first study to analyze DNA methylation on a genome scale in twins at birth, further highlighting the importance of the intrauterine environment on shaping the neonatal epigenome

Making Sense of the Epigenome Using Data Integration Approaches

Epigenetic research involves examining the mitotically heritable processes that regulate gene expression, independent of changes in the DNA sequence. Recent technical advances such as whole-genome bisulfite sequencing and affordable epigenomic array-based technologies, allow researchers to measure epigenetic profiles of large cohorts at a genome-wide level, generating comprehensive high-dimensional datasets that may contain important information for disease development and treatment opportunities. The epigenomic profile for a certain disease is often a result of the complex interplay between multiple genetic and environmental factors, which poses an enormous challenge to visualize and interpret these data. Furthermore, due to the dynamic nature of the epigenome, it is critical to determine causal relationships from the many correlated associations. In this review we provide an overview of recent data analysis approaches to integrate various omics layers to understand epigenetic mechanisms of complex diseases, such as obesity and cancer. We discuss the following topics: (i) advantages and limitations of major epigenetic profiling techniques, (ii) resources for standardization, annotation and harmonization of epigenetic data, and (iii) statistical methods and machine learning methods for establishing data-driven hypotheses of key regulatory mechanisms. Finally, we discuss the future directions for data integration that shall facilitate the discovery of epigenetic-based biomarkers and therapies.Peer reviewe

Leisure-time physical activity and DNA methylation agea twin study

BackgroundEpigenetic clocks may increase our understanding on human aging and how genetic and environmental factors regulate an individual aging process. One of the most promising clocks is Horvath's DNA methylation (DNAm) age. Age acceleration, i.e., discrepancy between DNAm age and chronological age, tells us whether the person is biologically young or old compared to his/her chronological age. Several environmental and lifestyle factors have been shown to affect life span. We investigated genetic and environmental predictors of DNAm age in young and older monozygotic (MZ) and dizygotic (DZ) twins with a focus on leisure time physical activity.ResultsQuantitative genetic modeling revealed that the relative contribution of non-shared environmental factors was larger among older compared with younger twin pairs [47% (95% CI 35, 63) vs. 26% (95% CI: 19, 35), pPeer reviewe