Acquired copy number variation in prostate tumours: a review of common somatic copy number alterations, how they are formed and their clinical utility.

Prostate cancer is one of the most commonly diagnosed cancers in men and unfortunately, disease will progress in up to a third of patients despite primary treatment. Currently, there is a significant lack of prognostic tests that accurately predict disease course; however, the acquisition of somatic chromosomal variation in the form of DNA copy number variants may help understand disease progression. Notably, studies have found that a higher burden of somatic copy number alterations (SCNA) correlates with more aggressive disease, recurrence after surgery and metastasis. Here we will review the literature surrounding SCNA formation, including the roles of key tumour suppressors and oncogenes (PTEN, BRCA2, NKX3.1, ERG and AR), and their potential to inform diagnostic and prognostic clinical testing to improve predictive value. Ultimately, SCNAs, or inherited germline alterations that predispose to SCNAs, could have significant clinical utility in diagnostic and prognostic tests, in addition to guiding therapeutic selection.

Maternal educational attainment in pregnancy and epigenome-wide DNA methylation changes in the offspring from birth until adolescence.

Maternal educational attainment (MEA) shapes offspring health through multiple potential pathways. Differential DNA methylation may provide a mechanistic understanding of these long-term associations. We aimed to quantify the associations of MEA with offspring DNA methylation levels at birth, in childhood and in adolescence. Using 37 studies from high-income countries, we performed meta-analysis of epigenome-wide association studies (EWAS) to quantify the associations of completed years of MEA at the time of pregnancy with offspring DNA methylation levels at birth (n = 9 881), in childhood (n = 2 017), and adolescence (n = 2 740), adjusting for relevant covariates. MEA was found to be associated with DNA methylation at 473 cytosine-phosphate-guanine sites at birth, one in childhood, and four in adolescence. We observed enrichment for findings from previous EWAS on maternal folate, vitamin-B12 concentrations, maternal smoking, and pre-pregnancy BMI. The associations were directionally consistent with MEA being inversely associated with behaviours including smoking and BMI. Our findings form a bridge between socio-economic factors and biology and highlight potential pathways underlying effects of maternal education. The results broaden our understanding of bio-social associations linked to differential DNA methylation in multiple early stages of life. The data generated also offers an important resource to help a more precise understanding of the social determinants of health.

Developmental origins of psycho-cardiometabolic multimorbidity in adolescence and their underlying pathways through methylation markers: a two-cohort study.

Understanding the biological mechanisms behind multimorbidity patterns in adolescence is important as they may act as intermediary risk factor for long-term health. We aimed to explore relationship between prenatal exposures and adolescent's psycho-cardiometabolic intermediary traits mediated through epigenetic biomarkers, using structural equation modeling (SEM). We used data from mother-child dyads from pregnancy and adolescents at 16-17 years from two prospective cohorts: Northern Finland Birth Cohort 1986 (NFBC1986) and Raine Study from Australia. Factor analysis was applied to generate two different latent factor structures: (a) prenatal exposures and (b) adolescence psycho-cardiometabolic intermediary traits. Furthermore, three types of epigenetic biomarkers were included: (1) DNA methylation score for maternal smoking during pregnancy (DNAmMSS), (2) DNAm age estimate PhenoAge and (3) DNAm estimate for telomere length (DNAmTL). Similar factor structure was observed between both cohorts yielding three prenatal factors, namely BMI (Body Mass Index), SOP (Socio-Obstetric-Profile), and Lifestyle, and four adolescent factors: Anthropometric, Insulin-Triglycerides, Blood Pressure, and Mental health. In the SEM pathways, stronger direct effects of F1prenatal-BMI (NFBC1986 = ß: 0.27; Raine = ß: 0.39) and F2prenatal-SOP (ß: -0.11) factors were observed on adolescent psycho-cardiometabolic multimorbidity. We observed an indirect effect of prenatal latent factors through epigenetic markers on a psycho-cardiometabolic multimorbidity factor in Raine study (P < 0.05). The present study exemplifies an evidence-based approach in two different birth cohorts to demonstrate similar composite structure of prenatal exposures and psycho-cardiometabolic traits (despite cultural, social, and genetic differences) and a common plausible pathway between them through underlying epigenetic markers.

Childhood sleep health and epigenetic age acceleration in late adolescence: Cross-sectional and longitudinal analyses.

AIM: Investigate if childhood measures of sleep health are associated with epigenetic age acceleration in late adolescence. METHODS: Parent-reported sleep trajectories from age 5 to 17, self-reported sleep problems at age 17, and six measures of epigenetic age acceleration at age 17 were studied in 1192 young Australians from the Raine Study Gen2. RESULTS: There was no evidence for a relationship between the parent-reported sleep trajectories and epigenetic age acceleration (p ≥ 0.17). There was a positive cross-sectional relationship between self-reported sleep problem score and intrinsic epigenetic age acceleration at age 17 (b = 0.14, p = 0.04), which was attenuated after controlling for depressive symptom score at the same age (b = 0.08, p = 0.34). Follow-up analyses suggested this finding may represent greater overtiredness and intrinsic epigenetic age acceleration in adolescents with higher depressive symptoms. CONCLUSION: There was no evidence for a relationship between self- or parent-reported sleep health and epigenetic age acceleration in late adolescence after adjusting for depressive symptoms. Mental health should be considered as a potential confounding variable in future research on sleep and epigenetic age acceleration, particularly if subjective measures of sleep are used.

rs641738C>T near MBOAT7 is associated with liver fat, ALT and fibrosis in NAFLD: A meta-analysis.

BACKGROUND & AIMS: A common genetic variant near MBOAT7 (rs641738C>T) has been previously associated with hepatic fat and advanced histology in NAFLD; however, these findings have not been consistently replicated in the literature. We aimed to establish whether rs641738C>T is a risk factor across the spectrum of NAFLD and to characterise its role in the regulation of related metabolic phenotypes through a meta-analysis. METHODS: We performed a meta-analysis of studies with data on the association between rs641738C>T genotype and liver fat, NAFLD histology, and serum alanine aminotransferase (ALT), lipids or insulin. These included directly genotyped studies and population-level data from genome-wide association studies (GWAS). We performed a random effects meta-analysis using recessive, additive and dominant genetic models. RESULTS: Data from 1,066,175 participants (9,688 with liver biopsies) across 42 studies were included in the meta-analysis. rs641738C>T was associated with higher liver fat on CT/MRI (+0.03 standard deviations [95% CI 0.02-0.05], pz = 4.8×10-5) and diagnosis of NAFLD (odds ratio [OR] 1.17 [95% CI 1.05-1.3], pz = 0.003) in Caucasian adults. The variant was also positively associated with presence of advanced fibrosis (OR 1.22 [95% CI 1.03-1.45], pz = 0.021) in Caucasian adults using a recessive model of inheritance (CC + CT vs. TT). Meta-analysis of data from previous GWAS found the variant to be associated with higher ALT (pz = 0.002) and lower serum triglycerides (pz = 1.5×10-4). rs641738C>T was not associated with fasting insulin and no effect was observed in children with NAFLD. CONCLUSIONS: Our study validates rs641738C>T near MBOAT7 as a risk factor for the presence and severity of NAFLD in individuals of European descent. LAY SUMMARY: Fatty liver disease is a common condition where fat builds up in the liver, which can cause liver inflammation and scarring (including 'cirrhosis'). It is closely linked to obesity and diabetes, but some genes are also thought to be important. We did this study to see whether one specific change ('variant') in one gene ('MBOAT7') was linked to fatty liver disease. We took data from over 40 published studies and found that this variant near MBOAT7 is linked to more severe fatty liver disease. This means that drugs designed to work on MBOAT7 could be useful for treating fatty liver disease.

Heritability of 596 lipid species and genetic correlation with cardiovascular traits in the Busselton Family Heart Study.

CVD is the leading cause of death worldwide, and genetic investigations into the human lipidome may provide insight into CVD risk. The aim of this study was to estimate the heritability of circulating lipid species and their genetic correlation with CVD traits. Targeted lipidomic profiling was performed on 4,492 participants from the Busselton Family Heart Study to quantify the major fatty acids of 596 lipid species from 33 classes. We estimated narrow-sense heritabilities of lipid species/classes and their genetic correlations with eight CVD traits: BMI, HDL-C, LDL-C, triglycerides, total cholesterol, waist-hip ratio, systolic blood pressure, and diastolic blood pressure. We report heritabilities and genetic correlations of new lipid species/subclasses, including acylcarnitine (AC), ubiquinone, sulfatide, and oxidized cholesteryl esters. Over 99% of lipid species were significantly heritable (h2: 0.06-0.50) and all lipid classes were significantly heritable (h2: 0.14-0.50). The monohexosylceramide and AC classes had the highest median heritabilities (h2 = 0.43). The largest genetic correlation was between clinical triglycerides and total diacylglycerol (rg = 0.88). We observed novel positive genetic correlations between clinical triglycerides and phosphatidylglycerol species (rg: 0.64-0.82), and HDL-C and alkenylphosphatidylcholine species (rg: 0.45-0.74). Overall, 51% of the 4,768 lipid species-CVD trait genetic correlations were statistically significant after correction for multiple comparisons. This is the largest lipidomic study to address the heritability of lipids and their genetic correlation with CVD traits. Future work includes identifying putative causal genetic variants for lipid species and CVD using genome-wide SNP and whole-genome sequencing data.

Bile acids associate with specific gut microbiota, low-level alcohol consumption and liver fibrosis in patients with non-alcoholic fatty liver disease.

BACKGROUND: Bile acids (BAs) are synthesized by the liver and modified by gut bacteria, and may play an intermediary role between the gut microbiome and liver in promoting fibrosis in non-alcoholic fatty liver disease (NAFLD). We investigated the associations between serum and faecal BAs, gut microbiome and fibrosis in patients with and without NAFLD and examined the impact of diet and alcohol consumption on these relationships. METHODS: Adult patients (n = 122) underwent liver biopsy and BAs characterization by high-performance liquid chromatography/mass spectrometry. Gut microbiome composition was analysed using next-generation 16S rRNA sequencing. Diet and alcohol intake were determined by 3-day food diary. RESULTS: Serum and faecal BA concentrations increased progressively among non-NAFLD controls (n = 55), NAFLD patients with no/mild fibrosis (F0-2, n = 58) and NAFLD with advanced fibrosis (F3/4, n = 9). Progressive increases in serum BAs were driven by primary conjugated BAs including glycocholic acid [GCA] and secondary conjugated BAs. In contrast, faecal BA increase was driven by secondary unconjugated BAs (predominately deoxycholic acid [DCA]). Serum GCA levels and faecal DCA levels correlated with the abundance of Bacteroidaceae and Lachnospiraceae, and stool secondary BAs with an unclassifiable family of the order Bacteroidales (Bacteroidales;other). These bacterial taxa were also associated with advanced fibrosis. Modest alcohol consumption was positively correlated with faecal DCA levels and relative abundance of Lachnospiracaea and Bacteroidales;other. CONCLUSIONS: Higher serum and faecal BA levels are associated with advanced fibrosis in NAFLD. Specific gut bacteria link alterations in BA profiles and advanced fibrosis, and may be influenced by low-level alcohol consumption.

Butyrate generated by gut microbiota and its therapeutic role in metabolic syndrome.

Metabolic syndrome (MetS) and the associated incidence of cardiovascular disease and type 2 diabetes represents a significant contributor to morbidity and mortality worldwide. Butyrate, a short-chain fatty acid produced by the gut microbiome, has long been known to promote growth in farmed animals and more recently has been reported to improve body weight and composition, lipid profile, insulin sensitivity and glycaemia in animal models of MetS. In vitro studies have examined the influence of butyrate on intestinal cells, adipose tissue, skeletal muscle, hepatocytes, pancreatic islets and blood vessels, highlighting genes and pathways that may contribute to its beneficial effects. Butyrate's influences in these cells have been attributed primarily to its epigenetic effects as a histone deacetylase inhibitor, as well as its role as an agonist of free fatty acid receptors, but clear mechanistic evidence is lacking. There is also uncertainty whether results from animal studies can translate to human trials due to butyrate's poor systemic availability and rapid clearance. Hitherto, several small-scale human clinical trials have failed to show significant benefits in MetS patients. Further trials are clearly needed, including with formulations designed to improve butyrate's availability. Regardless, dietary intervention to increase the rate of butyrate production may be a beneficial addition to current treatment. This review outlines the current body of evidence on the suitability of butyrate supplementation for MetS, looking at mechanistic effects on the various components of MetS and highlighting gaps in the knowledge and roadblocks to its use in humans.

Epigenome-wide meta-analysis of DNA methylation and childhood asthma.

BACKGROUND: Epigenetic mechanisms, including methylation, can contribute to childhood asthma. Identifying DNA methylation profiles in asthmatic patients can inform disease pathogenesis. OBJECTIVE: We sought to identify differential DNA methylation in newborns and children related to childhood asthma. METHODS: Within the Pregnancy And Childhood Epigenetics consortium, we performed epigenome-wide meta-analyses of school-age asthma in relation to CpG methylation (Illumina450K) in blood measured either in newborns, in prospective analyses, or cross-sectionally in school-aged children. We also identified differentially methylated regions. RESULTS: In newborns (8 cohorts, 668 cases), 9 CpGs (and 35 regions) were differentially methylated (epigenome-wide significance, false discovery rate < 0.05) in relation to asthma development. In a cross-sectional meta-analysis of asthma and methylation in children (9 cohorts, 631 cases), we identified 179 CpGs (false discovery rate < 0.05) and 36 differentially methylated regions. In replication studies of methylation in other tissues, most of the 179 CpGs discovered in blood replicated, despite smaller sample sizes, in studies of nasal respiratory epithelium or eosinophils. Pathway analyses highlighted enrichment for asthma-relevant immune processes and overlap in pathways enriched both in newborns and children. Gene expression correlated with methylation at most loci. Functional annotation supports a regulatory effect on gene expression at many asthma-associated CpGs. Several implicated genes are targets for approved or experimental drugs, including IL5RA and KCNH2. CONCLUSION: Novel loci differentially methylated in newborns represent potential biomarkers of risk of asthma by school age. Cross-sectional associations in children can reflect both risk for and effects of disease. Asthma-related differential methylation in blood in children was substantially replicated in eosinophils and respiratory epithelium.

Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium.

Pre-pregnancy maternal obesity is associated with adverse offspring outcomes at birth and later in life. Individual studies have shown that epigenetic modifications such as DNA methylation could contribute. Within the Pregnancy and Childhood Epigenetics (PACE) Consortium, we meta-analysed the association between pre-pregnancy maternal BMI and methylation at over 450,000 sites in newborn blood DNA, across 19 cohorts (9,340 mother-newborn pairs). We attempted to infer causality by comparing the effects of maternal versus paternal BMI and incorporating genetic variation. In four additional cohorts (1,817 mother-child pairs), we meta-analysed the association between maternal BMI at the start of pregnancy and blood methylation in adolescents. In newborns, maternal BMI was associated with small (<0.2% per BMI unit (1 kg/m2), P < 1.06 × 10-7) methylation variation at 9,044 sites throughout the genome. Adjustment for estimated cell proportions greatly attenuated the number of significant CpGs to 104, including 86 sites common to the unadjusted model. At 72/86 sites, the direction of the association was the same in newborns and adolescents, suggesting persistence of signals. However, we found evidence for acausal intrauterine effect of maternal BMI on newborn methylation at just 8/86 sites. In conclusion, this well-powered analysis identified robust associations between maternal adiposity and variations in newborn blood DNA methylation, but these small effects may be better explained by genetic or lifestyle factors than a causal intrauterine mechanism. This highlights the need for large-scale collaborative approaches and the application of causal inference techniques in epigenetic epidemiology.

Differential SLC6A4 methylation: a predictive epigenetic marker of adiposity from birth to adulthood.

BACKGROUND: The early life environment may influence susceptibility to obesity and metabolic disease in later life through epigenetic processes. SLC6A4 is an important mediator of serotonin bioavailability, and has a key role in energy balance. We tested the hypothesis that methylation of the SLC6A4 gene predicts adiposity across the life course. METHODS: DNA methylation at 5 CpGs within the SLC6A4 gene identified from a previous methyl binding domain array was measured by pyrosequencing. We measured DNA methylation in umbilical cord (UC) from children in the Southampton Women's Survey cohort (n = 680), in peripheral blood from adolescents in the Western Australian Pregnancy Cohort Study (n = 812), and in adipose tissue from lean and obese adults from the UK BIOCLAIMS cohort (n = 81). Real-time PCR was performed to assess whether there were corresponding alterations in gene expression in the adipose tissue. RESULTS: Lower UC methylation of CpG5 was associated with higher total fat mass at 4 years (p = 0.031), total fat mass at 6-7 years (p = 0.0001) and % fat mass at 6-7 years (p = 0.004). Lower UC methylation of CpG5 was also associated with higher triceps skinfold thickness at birth (p = 0.013), 6 months (p = 0.038), 12 months (p = 0.062), 2 years (p = 0.0003), 3 years (p = 0.00004) and 6-7 years (p = 0.013). Higher maternal pregnancy weight gain (p = 0.046) and lower parity (p = 0.029) were both associated with lower SLC6A4 CpG5 methylation. In adolescents, lower methylation of CpG5 in peripheral blood was associated with greater concurrent measures of adiposity including BMI (p ≤ 0.001), waist circumference (p = 0.011), subcutaneous fat (p ≤ 0.001) and subscapular, abdominal and suprailiac skinfold thicknesses (p = 0.002, p = 0.008, p = 0.004, respectively). In adipose tissue, methylation of both SLC6A4 CpG5 (p = 0.019) and expression of SLC6A4 (p = 0.008) was lower in obese compared with lean adults. CONCLUSIONS: These data suggest that altered methylation of CpG loci within SLC6A4 may provide a robust marker of adiposity across the life course.

Identification of novel sarcoma risk genes using a two-stage genome wide DNA sequencing strategy in cancer cluster families and population case and control cohorts.

BACKGROUND: Although familial clustering of cancers is relatively common, only a small proportion of familial cancer risk can be explained by known cancer predisposition genes. METHODS: In this study we employed a two-stage approach to identify candidate sarcoma risk genes. First, we conducted whole exome sequencing in three multigenerational cancer families ascertained through a sarcoma proband (n = 19) in order to prioritize candidate genes for validation in an independent case-control cohort of sarcoma patients using family-based association and segregation analysis. The second stage employed a burden analysis of rare variants within prioritized candidate genes identified from stage one in 560 sarcoma cases and 1144 healthy ageing controls, for which whole genome sequence was available. RESULTS: Variants from eight genes were identified in stage one. Following gene-based burden testing and after correction for multiple testing, two of these genes, ABCB5 and C16orf96, were determined to show statistically significant association with cancer. The ABCB5 gene was found to have a higher burden of putative regulatory variants (OR = 4.9, p-value = 0.007, q-value = 0.04) based on allele counts in sarcoma cases compared to controls. C16orf96, was found to have a significantly lower burden (OR = 0.58, p-value = 0.0004, q-value = 0.003) of regulatory variants in controls compared to sarcoma cases. CONCLUSIONS: Based on these genetic association data we propose that ABCB5 and C16orf96 are novel candidate risk genes for sarcoma. Although neither of these two genes have been previously associated with sarcoma, ABCB5 has been shown to share clinical drug resistance associations with melanoma and leukaemia and C16orf96 shares regulatory elements with genes that are involved with TNF-alpha mediated apoptosis in a p53/TP53-dependent manner. Future genetic studies in other family and population cohorts will be required for further validation of these novel findings.

Pleiotropy of cardiometabolic syndrome with obesity-related anthropometric traits determined using empirically derived kinships from the Busselton Health Study.

Over two billion adults are overweight or obese and therefore at an increased risk of cardiometabolic syndrome (CMS). Obesity-related anthropometric traits genetically correlated with CMS may provide insight into CMS aetiology. The aim of this study was to utilise an empirically derived genetic relatedness matrix to calculate heritabilities and genetic correlations between CMS and anthropometric traits to determine whether they share genetic risk factors (pleiotropy). We used genome-wide single nucleotide polymorphism (SNP) data on 4671 Busselton Health Study participants. Exploiting both known and unknown relatedness, empirical kinship probabilities were estimated using these SNP data. General linear mixed models implemented in SOLAR were used to estimate narrow-sense heritabilities (h 2) and genetic correlations (r g) between 15 anthropometric and 9 CMS traits. Anthropometric traits were adjusted by body mass index (BMI) to determine whether the observed genetic correlation was independent of obesity. After adjustment for multiple testing, all CMS and anthropometric traits were significantly heritable (h 2 range 0.18-0.57). We identified 50 significant genetic correlations (r g range: - 0.37 to 0.75) between CMS and anthropometric traits. Five genetic correlations remained significant after adjustment for BMI [high density lipoprotein cholesterol (HDL-C) and waist-hip ratio; triglycerides and waist-hip ratio; triglycerides and waist-height ratio; non-HDL-C and waist-height ratio; insulin and iliac skinfold thickness]. This study provides evidence for the presence of potentially pleiotropic genes that affect both anthropometric and CMS traits, independently of obesity.

Epigenetics, heritability and longitudinal analysis.

BACKGROUND: Longitudinal data and repeated measurements in epigenome-wide association studies (EWAS) provide a rich resource for understanding epigenetics. We summarize 7 analytical approaches to the GAW20 data sets that addressed challenges and potential applications of phenotypic and epigenetic data. All contributions used the GAW20 real data set and employed either linear mixed effect (LME) models or marginal models through generalized estimating equations (GEE). These contributions were subdivided into 3 categories: (a) quality control (QC) methods for DNA methylation data; (b) heritability estimates pretreatment and posttreatment with fenofibrate; and (c) impact of drug response pretreatment and posttreatment with fenofibrate on DNA methylation and blood lipids. RESULTS: Two contributions addressed QC and identified large statistical differences with pretreatment and posttreatment DNA methylation, possibly a result of batch effects. Two contributions compared epigenome-wide heritability estimates pretreatment and posttreatment, with one employing a Bayesian LME and the other using a variance-component LME. Density curves comparing these studies indicated these heritability estimates were similar. Another contribution used a variance-component LME to depict the proportion of heritability resulting from a genetic and shared environment. By including environmental exposures as random effects, the authors found heritability estimates became more stable but not significantly different. Two contributions investigated treatment response. One estimated drug-associated methylation effects on triglyceride levels as the response, and identified 11 significant cytosine-phosphate-guanine (CpG) sites with or without adjusting for high-density lipoprotein. The second contribution performed weighted gene coexpression network analysis and identified 6 significant modules of at least 30 CpG sites, including 3 modules with topological differences pretreatment and posttreatment. CONCLUSIONS: Four conclusions from this GAW20 working group are: (a) QC measures are an important consideration for EWAS studies that are investigating multiple time points or repeated measurements; (b) application of heritability estimates between time points for individual CpG sites is a useful QC measure for DNA methylation studies; (c) drug intervention demonstrated strong epigenome-wide DNA methylation patterns across the 2 time points; and (d) new statistical methods are required to account for the environmental contributions of DNA methylation across time. These contributions demonstrate numerous opportunities exist for the analysis of longitudinal data in future epigenetic studies.

Epigenetic effects of metformin: From molecular mechanisms to clinical implications.

There is a growing body of evidence that links epigenetic modifications to type 2 diabetes. Researchers have more recently investigated effects of commonly used medications, including those prescribed for diabetes, on epigenetic processes. This work reviews the influence of the widely used antidiabetic drug metformin on epigenomics, microRNA levels and subsequent gene expression, and potential clinical implications. Metformin may influence the activity of numerous epigenetic modifying enzymes, mostly by modulating the activation of AMP-activated protein kinase (AMPK). Activated AMPK can phosphorylate numerous substrates, including epigenetic enzymes such as histone acetyltransferases (HATs), class II histone deacetylases (HDACs) and DNA methyltransferases (DNMTs), usually resulting in their inhibition; however, HAT1 activity may be increased. Metformin has also been reported to decrease expression of multiple histone methyltransferases, to increase the activity of the class III HDAC SIRT1 and to decrease the influence of DNMT inhibitors. There is evidence that these alterations influence the epigenome and gene expression, and may contribute to the antidiabetic properties of metformin and, potentially, may protect against cancer, cardiovascular disease, cognitive decline and aging. The expression levels of numerous microRNAs are also reportedly influenced by metformin treatment and may confer antidiabetic and anticancer activities. However, as the reported effects of metformin on epigenetic enzymes act to both increase and decrease histone acetylation, histone and DNA methylation, and gene expression, a significant degree of uncertainty exists concerning the overall effect of metformin on the epigenome, on gene expression, and on the subsequent effect on the health of metformin users.

Longitudinal analytical approaches to genetic data.

BACKGROUND: Longitudinal phenotypic data provides a rich potential resource for genetic studies which may allow for greater understanding of variants and their covariates over time. Herein, we review 3 longitudinal analytical approaches from the Genetic Analysis Workshop 19 (GAW19). These contributions investigated both genome-wide association (GWA) and whole genome sequence (WGS) data from odd numbered chromosomes on up to 4 time points for blood pressure-related phenotypes. The statistical models used included generalized estimating equations (GEEs), latent class growth modeling (LCGM), linear mixed-effect (LME), and variance components (VC). The goal of these analyses was to test statistical approaches that use repeat measurements to increase genetic signal for variant identification. RESULTS: Two analytical methods were applied to the GAW19: GWA using real phenotypic data, and one approach to WGS using 200 simulated replicates. The first GWA approach applied a GEE-based model to identify gene-based associations with 4 derived hypertension phenotypes. This GEE model identified 1 significant locus, GRM7, which passed multiple test corrections for 2 hypertension-derived traits. The second GWA approach employed the LME to estimate genetic associations with systolic blood pressure (SBP) change trajectories identified using LCGM. This LCGM method identified 5 SBP trajectories and association analyses identified a genome-wide significant locus, near ATOX1 (p = 1.0E(-8)). Finally, a third VC-based model using WGS and simulated SBP phenotypes that constrained the ß coefficient for a genetic variant across each time point was calculated and compared to an unconstrained approach. This constrained VC approach demonstrated increased power for WGS variants of moderate effect, but when larger genetic effects were present, averaging across time points was as effective. CONCLUSION: In this paper, we summarize 3 GAW19 contributions applying novel statistical methods and testing previously proposed techniques under alternative conditions for longitudinal genetic association. We conclude that these approaches when appropriately applied have the potential to: (a) increase statistical power; (b) decrease trait heterogeneity and standard error;

Paternal Genetic Structure in Contemporary Mennonite Communities from the American Midwest.

Over the last 35 years, researchers from the Laboratory of Biological Anthropology at the University of Kansas have been working with Mennonite communities to better understand evolutionary patterns of fission-fusion in relationship to their genetic history and population structure. In this study, short tandem repeat (STR) markers from the nonrecombining region of the Y chromosome (NRY) provided increased resolution of the molecular population structure for these groups. NRY is known to be informative for determining paternal genetic ancestral patterns in recently derived human populations. Mennonites represent a branch of the Anabaptist movement that began in northern and central Europe in the 16th century and maintain a well-documented migration and genealogical history. Provided this historical information, we investigated the genetic relationship of 15 NRY STR loci within five Mennonite communities from Kansas (Goessel, Lone Tree, Garden View, and Meridian) and Nebraska (Henderson). We sought to determine if patterns of fission/fusion along familial lines persisted with paternal genetic information as evidenced through other classical genetic polymorphisms and molecular markers. NRY haplotype information was obtained for 94 individuals, and genetic variation was analyzed and compared across the five study populations and comparative Anabaptist and European populations. NRY haplogroups were assigned using a Bayesian allele frequency approach with 14 STR loci. A total of 92 NRY haplotypes were detected, with none shared across these communities. The most prevalent NRY haplogroup was R1b, which occurred in 56% of the entire sample. Eight additional NRY haplogroups (E1b1b, G2a, I1, I2, J2a1, L, Q, and R1a) were detected in smaller frequencies. Principal component analysis of NRY data, in contrast to mitochondrial DNA data, displayed no patterns of population subdivision of these congregations into communities. These NRY genetic profiles provide additional information regarding the recent migratory history of Mennonite communities and additional evidence for fission along paternal lines after migration to the United States.

A genome-wide integrative genomic study localizes genetic factors influencing antibodies against Epstein-Barr virus nuclear antigen 1 (EBNA-1).

Infection with Epstein-Barr virus (EBV) is highly prevalent worldwide, and it has been associated with infectious mononucleosis and severe diseases including Burkitt lymphoma, Hodgkin lymphoma, nasopharyngeal lymphoma, and lymphoproliferative disorders. Although EBV has been the focus of extensive research, much still remains unknown concerning what makes some individuals more sensitive to infection and to adverse outcomes as a result of infection. Here we use an integrative genomics approach in order to localize genetic factors influencing levels of Epstein Barr virus (EBV) nuclear antigen-1 (EBNA-1) IgG antibodies, as a measure of history of infection with this pathogen, in large Mexican American families. Genome-wide evidence of both significant linkage and association was obtained on chromosome 6 in the human leukocyte antigen (HLA) region and replicated in an independent Mexican American sample of large families (minimum p-value in combined analysis of both datasets is 1.4×10(-15) for SNPs rs477515 and rs2516049). Conditional association analyses indicate the presence of at least two separate loci within MHC class II, and along with lymphocyte expression data suggest genes HLA-DRB1 and HLA-DQB1 as the best candidates. The association signals are specific to EBV and are not found with IgG antibodies to 12 other pathogens examined, and therefore do not simply reveal a general HLA effect. We investigated whether SNPs significantly associated with diseases in which EBV is known or suspected to play a role (namely nasopharyngeal lymphoma, Hodgkin lymphoma, systemic lupus erythematosus, and multiple sclerosis) also show evidence of associated with EBNA-1 antibody levels, finding an overlap only for the HLA locus, but none elsewhere in the genome. The significance of this work is that a major locus related to EBV infection has been identified, which may ultimately reveal the underlying mechanisms by which the immune system regulates infection with this pathogen.

Longitudinal data analysis for genetic studies in the whole-genome sequencing era.

The analysis of whole-genome sequence (WGS) data using longitudinal phenotypes offers a potentially rich resource for the examination of the genetic variants and their covariates that affect complex phenotypes over time. We summarize eight contributions to the Genetic Analysis Workshop 18, which applied a diverse array of statistical genetic methods to analyze WGS data in combination with data from genome-wide association studies (GWAS) from up to four different time points on blood pressure phenotypes. The common goal of these analyses was to develop and apply appropriate methods that utilize longitudinal repeated measures to potentially increase the analytic efficiency of WGS and GWAS data. These diverse methods can be grouped into two categories, based on the way they model dependence structures: (1) linear mixed-effects (LME) models, where the random effect terms in the linear models are used to capture the dependence structures; and (2) variance-components models, where the dependence structures are constructed directly based on multiple components of variance-covariance matrices for the multivariate Gaussian responses. Despite the heterogeneous nature of these analytical methods, the group came to the following conclusions: (1) the use of repeat measurements can gain power to identify variants associated with the phenotype; (2) the inclusion of family data may correct genotyping errors and allow for more accurate detection of rare variants than using unrelated individuals only; and (3) fitting mixed-effects and variance-components models for longitudinal data presents computational challenges. The challenges and computational burden demanded by WGS data were addressed in the eight contributions.

Meta-analysis of human methylation data for evidence of sex-specific autosomal patterns.

BACKGROUND: Several individual studies have suggested that autosomal CpG methylation differs by sex both in terms of individual CpG sites and global autosomal CpG methylation. However, these findings have been inconsistent and plagued by spurious associations due to the cross reactivity of CpG probes on commercial microarrays. We collectively analysed 76 published studies (n = 6,795) for sex-associated differences in both autosomal and sex chromosome CpG sites. RESULTS: Overall autosomal methylation profiles varied substantially by study, and we encountered substantial batch effects. We accounted for these by conducting random effects meta-analysis for individual autosomal CpG methylation associations. After excluding non-specific probes, we found 184 autosomal CpG sites differentially methylated by sex after correction for multiple testing. In line with previous studies, average beta differences were small. Many of the most significantly associated CpG probes were new. Of note was differential CpG methylation in the promoters of genes thought to be involved in spermatogenesis and male fertility, such as SLC9A2, SPESP1, CRISP2, and NUPL1. Pathway analysis revealed overrepresentation of genes differentially methylated by sex in several broad Gene Ontology biological processes, including RNA splicing and DNA repair. CONCLUSIONS: This study represents a comprehensive analysis of sex-specific methylation patterns. We demonstrate the existence of sex-specific methylation profiles and report a large number of novel DNA methylation differences in autosomal CpG sites between sexes.