Multiple Testing Threshold Research Articles

Perturbations in the blood metabolome up to a decade before prostate cancer diagnosis in 4387 matched case-control sets from the European Prospective Investigation into Cancer and Nutrition.

Measuring pre-diagnostic blood metabolites may help identify novel risk factors for prostate cancer. Using data from 4387 matched case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC) study, we investigated the associations of 148 individual metabolites and three previously defined metabolite patterns with prostate cancer risk. Metabolites were measured by liquid chromatography-mass spectrometry. Multivariable-adjusted conditional logistic regression was used to estimate the odds ratio per standard deviation increase in log metabolite concentration and metabolite patterns (OR1SD) for prostate cancer overall, and for advanced, high-grade, aggressive. We corrected for multiple testing using the Benjamini-Hochberg method. Overall, there were no associations between specific metabolites or metabolite patterns and overall, aggressive, or high-grade prostate cancer that passed the multiple testing threshold (padj <0.05). Six phosphatidylcholines (PCs) were inversely associated with advanced prostate cancer diagnosed at or within 10 years of blood collection. metabolite patterns 1 (64 PCs and three hydroxysphingomyelins) and 2 (two acylcarnitines, glutamate, ornithine, and taurine) were also inversely associated with advanced prostate cancer; when stratified by follow-up time, these associations were observed for diagnoses at or within 10 years of recruitment (OR1SD 0.80, 95% CI 0.66-0.96 and 0.76, 0.59-0.97, respectively) but were weaker after longer follow-up (0.95, 0.82-1.10 and 0.85, 0.67-1.06). Pattern 3 (8 lyso PCs) was associated with prostate cancer death (0.82, 0.68-0.98). Our results suggest that the plasma metabolite profile changes in response to the presence of prostate cancer up to a decade before detection of advanced-stage disease.

Using Alternative Definitions of Controls to Increase Statistical Power in GWAS.

Genome-wide association studies (GWAS) are often underpowered due to small effect sizes of common single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the greatest statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.

GENOMIC ARCHITECTURE OF FEMALE REPRODUCTIVE AGING

Abstract Female reproductive lifespan is characterised by declining ovarian reserve, but the underlying mechanism is poorly understood. Reproductive ageing is a multifactorial trait with both genetic and environmental modifiers. Our research uses genome-wide analyses to identify the genes and biological processes that govern female reproductive ageing. We have identified 290 genetic loci with relatively common variants (&amp;gt;0.1%) that are associated with timing of natural menopause, in a meta-analysis of &amp;gt;200,000 women in the ReproGen consortium. In combination these common variants explain around 12% of the variation in menopause timing. Women in the top 1% combined genetic risk centile for earlier menopause are approximately 5x more likely to have menopause before 40 years. A high genetic risk for earlier menopause in mothers, but not fathers, is also associated with increased de novo mutation rate in offspring. We assessed the role of rare (MAF&amp;lt;0.1%) protein-coding variants on ovarian function in data from 104,733 females in the UK Biobank using gene burden association tests. We identified nine genes with associations that passed our multiple testing threshold. Protein-truncating variants in ZNF518A were associated with earlier menopause (effect size 5.61 years, P=1.2x10-10), with an effect larger than for any previously reported gene or variant. Deleterious variants in SAMHD1 were associated with &amp;gt;1 year later menopause and were also a germline risk factor for cancer predisposition in males and females. Understanding the genetics of reproductive ageing is not only important for fertility, but also has implications for broader age-related health outcomes, such as cancer, diabetes and osteoporosis.

GENOMIC ARCHITECTURE OF FEMALE REPRODUCTIVE AGING

Abstract Female reproductive lifespan is characterised by declining ovarian reserve, but the underlying mechanism is poorly understood. Reproductive ageing is a multifactorial trait with both genetic and environmental modifiers. Our research uses genome-wide analyses to identify the genes and biological processes that govern female reproductive ageing. We have identified 290 genetic loci with relatively common variants (&amp;gt;0.1%) that are associated with timing of natural menopause, in a meta-analysis of &amp;gt;200,000 women in the ReproGen consortium. In combination these common variants explain around 12% of the variation in menopause timing. Women in the top 1% combined genetic risk centile for earlier menopause are approximately 5x more likely to have menopause before 40 years. A high genetic risk for earlier menopause in mothers, but not fathers, is also associated with increased de novo mutation rate in offspring. We assessed the role of rare (MAF&amp;lt;0.1%) protein-coding variants on ovarian function in data from 104,733 females in the UK Biobank using gene burden association tests. We identified nine genes with associations that passed our multiple testing threshold. Protein-truncating variants in ZNF518A were associated with earlier menopause (effect size 5.61 years, P=1.2x10-10), with an effect larger than for any previously reported gene or variant. Deleterious variants in SAMHD1 were associated with &amp;gt;1 year later menopause and were also a germline risk factor for cancer predisposition in males and females. Understanding the genetics of reproductive ageing is not only important for fertility, but also has implications for broader age-related health outcomes, such as cancer, diabetes and osteoporosis.

The inflammatory proteome and risk of atrial fibrillation: genetic insights into causal relevance

Abstract Background Cardiac and systemic inflammation have been associated with a higher risk of atrial fibrillation (AF) in both animal models and human studies. Causality, however, has been questioned due to inconsistent efficacy of anti-inflammatory treatments in preventing incident or recurrent AF, and potentially confounding associations with AF risk factors such as ischaemic heart disease. Inflammatory processes are highly complex and involve a large number of proteins, but the individual relevance and causal role of these for AF remains unclear. Purpose To explore the nature of the relationship between the inflammatory proteome and risk of AF. Methods Associations between 26 inflammatory proteins and AF were assessed in a two-sample Mendelian randomization (MR) framework, with primary MR causal estimates with AF estimated among 339,214 White British UK Biobank (UKB) participants (AF cases=30,630). MR analyses for each inflammatory protein included independent variants previously associated with the relevant protein at genome-wide significance (p&amp;lt;5x10-8) across the genome (trans-protein quantitative trait loci [pQTLs]), or restricted to at least 50kb from the closest upstream gene and 50 kb downstream from the target gene (cis-pQTLs). Sensitivity analyses to assess potential pleiotropy were conducted (MR-Egger, weighted median, and weighted mode). Associations passing multiple testing threshold (p&amp;lt;0.002) in UKB were further validated in meta-analyses with independent datasets including over 50,000 AF cases (FinnGen and AFGen). Research undertaken using UKB application 14568. Results This inflammatory protein-wide study identified three proteins that have support for causal associations with AF. Genetically-predicted levels of IL6R, CD40, and Chitinase-3-like protein 1 (YKL40) each showed a negative association with risk of AF, with up to a 5% lower AF risk per standard deviation higher genetically-predicted levels of these proteins (Figure 1). These findings were further confirmed in meta-analysis with data from AFGen and FinnGen. No evidence of pleiotropy was identified, and results were also confirmed in cis-pQTL analyses, which were fully consistent with the trans-pQTL analyses (Table 1). Analyses stratified by various baseline characteristics highlighted stronger causal estimates in those with higher levels of C-reactive protein (with interaction p-values &amp;lt;0.001). Conclusions Genetic approaches support the relevance of lifelong differences in the inflammatory proteome for AF, and causal relationships between specific inflammatory markers and risk of AF. Greater soluble IL6R and CD40 as measured in proteomic analyses are both associated with lower levels of inflammation. As previous work indicates that genetically upregulated CD40 and IL6R are similarly associated with a lower risk of ischemic stroke, the risk-benefit of directly targeting these pathways needs further consideration.Figure 1Table 1

Relationship between 233 colorectal cancer risk loci and survival in 1926 patients with advanced disease

BackgroundGenome, transcriptome and methylome-wide association studies have identified single-nucleotide polymorphisms (SNPs) or genes at 258 loci associated with colorectal cancer (CRC) risk. We studied the relationship between these and patient outcome.MethodsWe studied 1926 unrelated patients with advanced CRC from COIN and COIN-B. Of 205 CRC-risk SNPs, 19 were directly genotyped and 162 were imputed, and of 53 risk genes, 52 were tested. An additive Cox model for overall survival was adjusted for known prognostic factors. For nominally significant SNPs or genes, we considered a recessive model with a Bonferroni corrected threshold of P = 2.1 × 10−4. We examined SNPs as expression quantitative trait loci (eQTL) and the relationship between gene expression in colorectal tumours and survival in 597 unrelated patients.ResultsEleven SNPs or genes were nominally associated with survival under an additive model. Only rs117079142 mapping to UTP23 and EIF3H (Hazard Ratio [HR] = 2.79, 95% Confidence Intervals [CI] = 1.70–4.58, P = 4.7 × 10−5) and rs9924886 mapping to CDH1 and CDH3 (HR = 1.24, 95% CI = 1.12–1.38, P = 5.2 × 10−5) passed the multiple testing threshold under a recessive model. rs117079142 was an eQTL for UTP23 and rs9924886 for CDH1, CDH3 and ZFP90. Decreased CDH1 expression in CRCs was associated with worse survival (HR = 2.18, 95% CI = 1.3–3.5, P = 1.8 × 10−3).Conclusionrs117079142 and rs9924886 may represent potential prognostic biomarkers for CRC.

Large epigenome-wide association study identifies multiple novel differentially methylated CpG sites associated with suicidal thoughts and behaviors in veterans.

The U.S. suicide mortality rate has steadily increased during the past two decades, particularly among military veterans; however, the epigenetic basis of suicidal thoughts and behaviors (STB) remains largely unknown. To address this issue, we conducted an epigenome-wide association study of DNA methylation (DNAm) of peripheral blood samples obtained from 2,712 U.S. military veterans. Three DNAm probes were significantly associated with suicide attempts, surpassing the multiple testing threshold (FDR q-value <0.05), including cg13301722 on chromosome 7, which lies between the genes SLC4A2 and CDK5; cg04724646 in PDE3A; and cg04999352 in RARRES3. cg13301722 was also found to be differentially methylated in the cerebral cortex of suicide decedents in a publicly-available dataset (p = 0.03). Trait enrichment analysis revealed that the CpG sites most strongly associated with STB in the present sample were also associated with smoking, alcohol consumption, maternal smoking, and maternal alcohol consumption, whereas pathway enrichment analysis revealed significant associations with circadian rhythm, adherens junction, insulin secretion, and RAP-1 signaling, each of which was recently associated with suicide attempts in a large, independent genome-wide association study of suicide attempts of veterans. Taken together, the present findings suggest that SLC4A2, CDK5, PDE3A, and RARRES3 may play a role in STB. CDK5, a member of the cyclin-dependent kinase family that is highly expressed in the brain and essential for learning and memory, appears to be a particularly promising candidate worthy of future study; however, additional work is still needed to replicate these finding in independent samples.

COVID-19 and Thyroid Function: A Bi-Directional Two-Sample Mendelian Randomization Study.

Background: Thyroid dysfunction has been observed among some patients with coronavirus disease (COVID-19). It is unclear whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (or its severity) leads to the development of thyroid dysfunction, or vice versa. In this study, we examined the bi-directional causal relationship between host genetic liability to three COVID-19 phenotypes (including SARS-CoV-2 infection, hospitalized and severe COVID-19) and three thyroid dysfunction traits (including hyperthyroidism, hypothyroidism, and autoimmune thyroid disease [AITD]) and three continuous traits of thyroid hormones (including thyrotropin [TSH] and free thyroxine [fT4] within reference range, and TSH in full range). Methods: Summary statistics from the largest available meta-analyses of human genome-wide association studies were retrieved for the following variables: SARS-CoV-2 infection (n = 1,348,701), COVID-19 hospitalization (n = 1,557,411), severe COVID-19 (n = 1,059,456), hyperthyroidism (n = 51,823), hypothyroidism (n = 53,423), AITD (n = 755,406), TSH within reference range (n = 54,288), fT4 within reference range (n = 49,269), and TSH in full range (n = 119,715). Using a two-sample Mendelian randomization (MR) approach, the inverse-variance weighted (IVW) method was adopted as the main MR analysis. Weighted median, contamination mixture, MR-Egger, and MR pleiotropy residual sum and outlier (MR-PRESSO) methods were applied as sensitivity analyses. Results: Host genetic susceptibility to SARS-CoV-2 infection was causally associated with hypothyroidism in the main IVW analysis (per doubling in prevalence of SARS-CoV-2 infection, odds ratio [OR] = 1.335; 95% confidence interval [CI]: 1.167-1.526; p = 2.4 × 10-5, surpassing the Bonferroni multiple-testing threshold). Similar causal estimates were observed in the sensitivity analyses (weighted median: OR = 1.296; CI: 1.066-1.575; p = 9 × 10-3; contamination mixture: OR = 1.356; CI: 1.095-1.818; p = 0.013; MR-Egger: OR = 1.712; CI: 1.202-2.439; p = 2.92 × 10-3, and MR-PRESSO: OR = 1.335; CI: 1.156-1.542; p = 5.73 × 10-4). Host genetic liability to hospitalized or severe COVID-19 was not associated with thyroid dysfunction or thyroid hormone levels. In the reverse direction, there was no evidence to suggest that genetic predisposition to thyroid dysfunction or genetically determined thyroid hormone levels altered the risk of the COVID-19 outcomes. Conclusions: This bi-directional MR study supports that host response to SARS-CoV-2 viral infection plays a role in the causal association with increased risk of hypothyroidism. Long-term follow-up studies are needed to confirm the expected increased hypothyroidism risk.

Abstract 2283: SLC25A46 shows potential as a novel genetic regulator in breast cancer development

Abstract SLC25A46 is a part of the mitochondrial solute carrier family (SLC25) and acts as a transporter transferring lipids between the mitochondria and endoplasmic reticulum space. SLC25A46 is expressed in the mitochondrial outer membrane, where it plays a significant role in regulating mitochondrial dynamics, cristae maintenance, and mitochondrial respiratory function. SLC25A46 prevents the formation of hyperfilamentous mitochondria and interacts with novel mitochondrial fusion proteins such as MFN-2 and OPA1 and the cristae organizing complex, MICOS. Notably, research has shown that a first-in-class, small molecule-specific OPA1 inhibitor can be used pharmacologically to curtail tumor growth; however, the OPA1 inhibitor did not explore how the interacting partner, SLC25A46, was affected by such inhibition. Indeed, novel targets are needed for advanced breast cancers as a means of therapeutic interventions. Considering the critical role of SLC25A46, we sought to investigate novel mitochondrial proteins that are understudied in breast cancer. We applied a statistical framework to calculate predicted gene expression for SLC25A46 in 70,349 patients of European descent in BioVU, the Vanderbilt University Medical Center (VUMC) biorepository linked to de-identified electronic health records (EHRs). A genetically predicted gene expression model for SLC25A46 was trained on directly measured RNA-seq data across 17 tissues from the Genotype-Tissue Expression (GTEx) Project. We then fitted a multivariable logistic regression model to test SLC25A46 predicted expression against 1,704 phenotypes for each tissue. We observed that patients with high predicted expression of SLC25A46 were more likely to receive diagnosis of ‘abnormal findings in mammograms’ (P=2.76E-06, OR=2.26) in adipose subcutaneous tissues. Likewise, we found yet another significant association with ‘lump or mass in breast’ (P=8.9E-06, OR=2.61) in adipose subcutaneous tissues. These results pass their individual Bonferroni correction that was applied separately for each tissue, but fell short of passing a strict multiple testing threshold that accounted for all tissues. Given the association between SLC25A46 and abnormal phenotypes that are commonly coded for patients in relation to breast cancer, we conducted a linear regression model with SLC25A46 and ionized calcium and found a modest association (P=0.03, OR=1.02). Elevated serum levels of calcium are frequently observed in advanced breast cancer. Additionally, proteins that interact with SLC25A46 such as OPA1, are overexpressed in breast cancer. We further constructed a polygene score to determine the effects of these genes in all breast cancer phenotypes. Together, these data suggest that SLC25A46 has implications in breast cancer as a novel target in cancer development. Citation Format: Heather K. Beasley, Ky'Era V. Actkins, Tyne Miller-Flemming, Bret C. Mobley, Lea Davis, Antentor O. Hinton, Nancy J. Cox. SLC25A46 shows potential as a novel genetic regulator in breast cancer development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2283.

Longitudinal profiling of metabolic ageing trends in two population cohorts of young adults.

Quantification of metabolic changes over the human life course is essential to understanding ageing processes. Yet longitudinal metabolomics data are rare and long gaps between visits can introduce biases that mask true trends. We introduce new ways to process quantitative time-series population data and elucidate metabolic ageing trends in two large cohorts. Eligible participants included 1672 individuals from the Cardiovascular Risk in Young Finns Study and 3117 from the Northern Finland Birth Cohort 1966. Up to three time points (ages 24-49 years) were analysed by nuclear magnetic resonance metabolomics and clinical biochemistry (236 measures). Temporal trends were quantified as median change per decade. Sample quality was verified by consistency of shared biomarkers between metabolomics and clinical assays. Batch effects between visits were mitigated by a new algorithm introduced in this report. The results below satisfy multiple testing threshold of P < 0.0006. Women gained more weight than men (+6.5% vs +5.0%) but showed milder metabolic changes overall. Temporal sex differences were observed for C-reactive protein (women +5.1%, men +21.1%), glycine (women +5.2%, men +1.9%) and phenylalanine (women +0.6%, men +3.5%). In 566 individuals with ≥+3% weight gain vs 561 with weight change ≤-3%, divergent patterns were observed for insulin (+24% vs -10%), very-low-density-lipoprotein triglycerides (+32% vs -6%), high-density-lipoprotein2 cholesterol (-6.5% vs +4.7%), isoleucine (+5.7% vs -6.0%) and C-reactive protein (+25% vs -22%). We report absolute and proportional trends for 236 metabolic measures as new reference material for overall age-associated and specific weight-driven changes in real-world populations.

Diagnostic and Prognostic Value of Quantitative Computed Tomography Parameters of Adrenal Glands in Patients from Internistled ICU with Sepsis and Septic Shock

The aim was to prospectively evaluate the diagnostic and prognostic value of different quantitative analysis methods assessing adrenal gland parameters on contrast-enhanced CT scans in patients with septic conditions. Seventy–six patients (49 men, 27 women) received CT scans for focus search. Adrenal glands were analyzed by means of three different methods: subjective region of interest (ROI) measurement, organ segmentation and histogram analysis using semi-automated software. Univariate analyses with multiple testing thresholds and receiver operating characteristic curves were performed. Clinical endpoints were 8-days, 28-days and 6-months mortality. Forty-four CT scans were analyzed (ground truth: patients with no sepsis: n = 6; patients with sepsis: n = 15; patients in septic shock: n = 21). Left adrenal gland (LAG) values were analyzed and compared, as data variation was lower than in the right adrenal glands. In patients with septic conditions, the combination of high LAG and Inferior Vena Cava (IVC) density values was highly specific for septic shock with all three methods. Only segmentation values were significantly different between the sepsis and septic shock groups after confounder correction (p = 0.048). Total adrenal gland volume was 20% higher in the septic shock patients while a relatively small LAG volume within the septic shock subgroup was associated with higher mortality at day 8 (AUC = 0.8; p = 0.006) and at 6 months (AUC = 0.7; p = 0.035). However, time-consuming density analysis methods assessing adrenal glands do not provide additional diagnostic value in patients with septic conditions. The combination of high LAG and IVC attenuation values seems to be highly specific for septic shock, regardless of the analysis type. Adrenal gland volume reveals short- and long-term prognostic capacity.

Expression of markers of stem cell characteristics, epithelial-mesenchymal transition, basal-like phenotype, proliferation, and androgen receptor in metaplastic breast cancer and their prognostic impact

Background Metaplastic breast cancer (MpBC) is a heterogeneous subtype of invasive mammary carcinoma associated with epithelial-mesenchymal transition (EMT) and cancer stem cell characteristics. Data regarding prognostic markers and potentially actionable targets for therapy are still limited. The present study aimed to characterize the immunohistochemical landscape of this rare malignancy and to identify potential prognostic factors and targets for therapy. Material and methods A total of 75 patients diagnosed with MpBC over a 15-year period were included in the study. We performed immunohistochemical analyses for Ki-67 (MIB-1), epidermal growth factor receptor (EGFR), cytokeratin 5/6, vimentin, CD44, and androgen receptor (AR) and correlated their expression with clinicopathologic features and clinical outcomes. The p-values for survival analyses were corrected for multiple testing (threshold 0.01). Results Most tumors expressed CK5/6 (73%), EGFR (59%), CD44 (81%), and vimentin (87%). Eighty-nine percent had a high Ki-67 index. Eighty-four percent were classified as basal-like (CK 5/6 or EGFR positive). AR was expressed in 21% of the tumors. The basal-like phenotype was significantly (p = 0.009) associated with inferior disease-free (DFS) and breast-cancer-specific overall survival (BCOS) with borderline significance (p = 0.01). In addition, a low Ki-67 index was associated with improved DFS (p = 0.033) and BCOS (p = 0.03). Conclusion Most MpBCs express basal markers (CK5/6, EGFR), epithelial-mesenchymal transition marker vimentin, and the stem cell marker CD44. Expression of basal-like markers was significantly related to inferior DFS. All the 11 patients with a lack of expression of basal markers survived without relapse.

Alcohol Induced Depression: Clinical, Biological and Genetic Features.

Background: In clinical practice, there is the need to have clinical and biological markers to identify induced depression. The objective was to investigate clinical, biological and genetic differences between Primary Major Depression (Primary MD) and Alcohol Induced MD (AI-MD). Methods: Patients, of both genders, were recruited from psychiatric hospitalisation units. The PRISM instrument was used to establish the diagnoses. Data on socio-demographic/family history, clinical scales for depression, anxiety, personality and stressful life events were recorded. A blood test was performed analysing biochemical parameters and a Genome Wide Association Study (GWAS) to identify genetic markers associated with AI-MD. Results: A total of 80 patients were included (47 Primary MD and 33 AI-MD). The AI-MD group presented more medical comorbidities and less family history of depression. There were differences in traumatic life events, with higher scores in the AI-MD (14.21 ± 11.35 vs. 9.30 ± 7.38; p = 0.021). DSM-5 criteria were different between groups with higher prevalence of weight changes and less anhedonia, difficulties in concentration and suicidal thoughts in the AI-MD. None of the genetic variants reached significance beyond multiple testing thresholds; however, some suggestive variants were observed. Conclusions: This study has found clinical and biological features that may help physicians to identify AI-MD and improve its therapeutic approach.

Identifying epigenetic biomarkers of established prognostic factors and survival in a clinical cohort of individuals with oropharyngeal cancer

BackgroundSmoking status, alcohol consumption and HPV infection (acquired through sexual activity) are the predominant risk factors for oropharyngeal cancer and are thought to alter the prognosis of the disease. Here, we conducted single-site and differentially methylated region (DMR) epigenome-wide association studies (EWAS) of these factors, in addition to ∼ 3-year survival, using Illumina Methylation EPIC DNA methylation profiles from whole blood in 409 individuals as part of the Head and Neck 5000 (HN5000) study. Overlapping sites between each factor and survival were then assessed using two-step Mendelian randomization to assess whether methylation at these positions causally affected survival.ResultsUsing the MethylationEPIC array in an OPC dataset, we found novel CpG associations with smoking, alcohol consumption and ~ 3-year survival. We found no CpG associations below our multiple testing threshold associated with HPV16 E6 serological response (used as a proxy for HPV infection). CpG site associations below our multiple-testing threshold (PBonferroni < 0.05) for both a prognostic factor and survival were observed at four gene regions: SPEG (smoking), GFI1 (smoking), PPT2 (smoking) and KHDC3L (alcohol consumption). Evidence for a causal effect of DNA methylation on survival was only observed in the SPEG gene region (HR per SD increase in methylation score 1.28, 95% CI 1.14 to 1.43, P 2.12 × 10−05).ConclusionsPart of the effect of smoking on survival in those with oropharyngeal cancer may be mediated by methylation at the SPEG gene locus. Replication in data from independent datasets and data from HN5000 with longer follow-up times is needed to confirm these findings.

Comprehensive analysis of colorectal cancer-risk loci and survival outcome: A prognostic role for CDH1 variants

PurposeGenome-wide association studies have identified common single nucleotide polymorphisms (SNPs) at 83 loci associated with colorectal cancer (CRC) risk in European populations. Because germline variation can also influence patient outcome, we studied the relationship between these SNPs and CRC survivorship. Experimental designFor the 83 risk loci, 10 lead SNPs were directly genotyped, 72 were imputed and 1 was not genotyped nor imputed, in 1948 unrelated patients with advanced CRC from the clinical trials COIN and COIN–B (oxaliplatin and fluoropyrimidine chemotherapy ± cetuximab). A Cox survival model was used for each variant, and variants classified by pathway, adjusting for known prognostic factors. We imposed a Bonferroni threshold of P = 6.6 × 10−4 for multiple testing. We carried out meta-analyses of published risk SNPs associated with survival. ResultsUnivariate analysis identified six SNPs associated with overall survival (OS) (P < 0.05); however, only rs9939049 in CDH1 remained significant beyond the Bonferroni threshold (Hazard Ratio [HR] 1.44, 95% Confidence Intervals [CI]: 1.21–1.71, P = 5.0 × 10−5). Fine mapping showed that rs12597188 was the most significant SNP at this locus and remained significant after adjustment for known prognostic factors beyond multiple testing thresholds (HR 1.23, 95% CI: 1.13–1.34, P = 1.9 × 10−6). rs12597188 was also associated with poor response to therapy (OR 0.61, 95% CI: 0.42–0.87, P = 6.6 × 10−3). No combinations of SNPs within pathways were more significantly associated with survival compared with single variants alone, and no other risk SNPs were associated with survival in meta-analyses. ConclusionsThe CRC susceptibility SNP rs9939049 in CDH1 influences patient survival and warrants further evaluation as a prognostic biomarker.

Genetic analysis of hsCRP in American Indians: The Strong Heart Family Study.

BackgroundIncreased serum levels of C-reactive protein (CRP), an important component of the innate immune response, are associated with increased risk of cardiovascular disease (CVD). Multiple single nucleotide polymorphisms (SNP) have been identified which are associated with CRP levels, and Mendelian randomization studies have shown a positive association between SNPs increasing CRP expression and risk of colon cancer (but thus far not CVD). The effects of individual genetic variants often interact with the genetic background of a population and hence we sought to resolve the genetic determinants of serum CRP in a number of American Indian populations.MethodsThe Strong Heart Family Study (SHFS) has serum CRP measurements from 2428 tribal members, recruited as large families from three regions of the United States. Microsatellite markers and MetaboChip defined SNP genotypes were incorporated into variance components, decomposition-based linkage and association analyses.ResultsCRP levels exhibited significant heritability (h2 = 0.33 ± 0.05, p<1.3 X 10−20). A locus on chromosome (chr) 6, near marker D6S281 (approximately at 169.6 Mb, GRCh38/hg38) showed suggestive linkage (LOD = 1.9) to CRP levels. No individual SNPs were found associated with CRP levels after Bonferroni adjustment for multiple testing (threshold <7.77 x 10−7), however, we found nominal associations, many of which replicate previous findings at the CRP, HNF1A and 7 other loci. In addition, we report association of 46 SNPs located at 7 novel loci on chromosomes 2, 5, 6(2 loci), 9, 10 and 17, with an average of 15.3 Kb between SNPs and all with p-values less than 7.2 X 10−4.ConclusionIn agreement with evidence from other populations, these data show CRP serum levels are under considerable genetic influence; and include loci, such as near CRP and other genes, that replicate results from other ethnic groups. These findings also suggest possible novel loci on chr 6 and other chromosomes that warrant further investigation.

Searching for Signatures of Cold Climate Adaptation in TRPM8 Gene in Populations of East Asian Ancestry.

Dispersal of Homo sapiens across the globe during the last 200,000 years was accompanied by adaptation to local climatic conditions, with severe winter temperatures being probably one of the most significant selective forces. The TRPM8 gene codes for a cold-sensing ion channel, and adaptation to low temperatures is the major determinant of its molecular evolution. Here, our aim was to search for signatures of cold climate adaptation in TRPM8 gene using a combined data set of 19 populations of East Asian ancestry from the 1000 Genomes Project and Human Genome Diversity Project. As a result, out of a total of 60 markers under study, none showed significant association with the average winter temperatures at the locations of the studied populations considering the multiple testing thresholds. This might suggest that the principal mode of TRPM8 evolution may be different from widespread models, where adaptive alleles are additive, dominant or recessive, at least in populations with the predominant East Asian component. For example, evolution by means of selectively preferable epistatic interactions among amino acids may have taken place. Despite the lack of strong signals of association, however, a very promising single nucleotide polymorphism (SNP) was found. The SNP rs7577262 is considered the best candidate based on its allelic correlations with winter temperatures, signatures of selective sweep and physiological evidences. The second top SNP, rs17862920, may participate in adaptation as well. Additionally, to assist in interpreting the nominal associations, the other markers reached, we performed SNP prioritization based on functional evidences found in literature and on evolutionary conservativeness.

Abstract 4337: Identifying epigenetic biomarkers in a clinical cohort of individuals with oropharyngeal cancer

Abstract Oropharyngeal cancer (OPC) shows a distinct epidemiology to other head and neck cancer (HNC) subtypes. Several lifestyle and dietary factors as well as viral infections have been implicated in altering both incidence and prognosisfor OPC, notably smoking, alcohol consumption and HPV infection. We aimed to: 1) assess the impact of these epidemiological factors on epigenome-wide DNA methylation patterns, 2) evaluate whether DNA methylation patterns were associated with survival from OPC,3) ascertain whether novel exposure or prognostic indicators could be derived from DNA methylation patterns and 4)establish whether DNA methylation plays a causal role in mediating the impact of prognostic factors on survival.In a large prospective HNC cohort (Head and Neck 5000) we undertook epigenome-wide association study (EWAS) and differentially-methylated region (DMR) analyses of the aforementioned prognostic factors and mortality, using methylation data on &amp;gt;850.000 CpG sites measured using theIllumina MethylationEPIC on 420 individuals diagnosed with OPC . We performed multivariable linear regression analysis of DNA methylation against the prognostic factors, and Cox regression analysis of survival in relation to DNA methylation. We then determined the extent to which any results mediated the pathway between prognostic factors and OPC mortality using Mendelian randomization (MR).We identified CpG sites and DMRs associated with smoking and alcohol consumption below our multiple-testing threshold, but none with HPV positivity. We also identified 7 CpGs associated with survival (~3 years post-diagnosis), independent of smoking, alcohol consumption and HPV positivity. 18 CpGs across 3 DMRs were found to be associated with both smoking and mortality and 5 CpGswithin 1 DMR were identified in relation to both alcohol and mortality. We hypothesised that for these CpG sites there could be a mediating effect of DNA methylation, whereby DNA methylation mediates the association between the prognostic factor and OPC mortality. Using an inverse-variance weighted (IVW) MR approachto investigate the causal effect of DNA methylation at the identified sites, we found that hypomethylation in CpGslocated within a DMR associated with smoking (Chr2:220325443-220326041; annotating to the SPEG gene) showed some evidence of a causal effect on increased mortality (HR: 1.15, 95% CI: 1.05 to 1.25, P: 1.12x10-3). Within the context of OPC, we found novel epigenetic biomarkers measured by the Illumina MethylationEPIC array to be associated with the prognostic factors of smoking and alcohol, and with mortality, respectively. We also found preliminary evidence of a potential mediating effect of DNA methylation at the SPEG gene, between smoking and OPC mortality. However, longer follow up in Head and Neck 5000 and suitable replication data is needed to strengthen the validity of these findings. Citation Format: Ryan Langdon. Identifying epigenetic biomarkers in a clinical cohort of individuals with oropharyngeal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4337.

Targeted Resequencing of the Coding Sequence of 38 Genes Near Breast Cancer GWAS Loci in a Large Case-Control Study.

Genes regulated by breast cancer risk alleles identified through genome-wide association studies (GWAS) may harbor rare coding risk alleles. We sequenced the coding regions for 38 genes within 500 kb of 38 lead GWAS SNPs in 13,538 breast cancer cases and 5,518 controls. Truncating variants in these genes were rare, and were not associated with breast cancer risk. Burden testing of rare missense variants highlighted 5 genes with some suggestion of an association with breast cancer, although none met the multiple testing thresholds: MKL1, FTO, NEK10, MDM4, and COX11. Six common alleles in COX11, MAP3K1 (two), and NEK10 (three) were associated at the P < 0.0001 significance level, but these likely reflect linkage disequilibrium with causal regulatory variants. There was no evidence that rare coding variants in these genes confer substantial breast cancer risks. However, more modest effect sizes could not be ruled out. We tested the hypothesis that rare variants in 38 genes near breast cancer GWAS loci may mediate risk. These variants do not appear to play a major role in breast cancer heritability.

Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study.

Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer-metabolite associations using two-sample Mendelian randomization (MR). The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal. We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk. The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.