Genetic architecture of cancer and other complex diseases: lessons learned and future directions

An Overview of Cancer Biology, Pathophysiological Development and It's Treatment Modalities: Current Challenges of Cancer anti-Angiogenic Therapy

A number of conditions and factors can cause the transformation of normal cells in the body into malignant tissue by changing the normal functions of a wide range of regulatory, apoptotic, and signal transduction pathways. Despite the current deficiency in fully understanding the mechanism of cancer action accurately and clearly, numerous genes and proteins that are causally involved in the initiation, progression, and metastasis of cancer have been identified. But due to the lack of space and the abundance of details on this complex topic, we have emphasized here more recent advances in our understanding of the principles implied tumor cell transformation, development, invasion, angiogenesis, and metastasis. Inhibition of angiogenesis is a significant strategy for the treatment of various solid tumors, that essentially depend on cutting or at least limiting the supply of blood to micro-regions of tumors, leading to pan-hypoxia and pan-necrosis inside solid tumor tissues. Researchers have continued to enhance the efficiency of anti-angiogenic drugs over the past two decades, to identify their potential in the drug interaction, and to discover reasonable interpretations for possible resistance to treatment. In this review, we have discussed an overview of cancer history and recent methods use in cancer therapy, focusing on anti-angiogenic inhibitors targeting angiogenesis formation. Further, this review has explained the molecular mechanism of action of these anti-angiogenic inhibitors in various tumor types and their limitations use. In addition, we described the synergistic mechanisms of immunotherapy and anti-angiogenic therapy and summarizes current clinical trials of these combinations. Many phase III trials found that combining immunotherapy and anti-angiogenic therapy improved survival. Therefore, targeting the source supply of cancer cells to grow and spread with new anti-angiogenic agents in combination with different conventional therapy is a novel method to reduce cancer progression. The aim of this paper is to overview the varying concepts of cancer focusing on mechanisms involved in tumor angiogenesis and provide an overview of the recent trends in anti-angiogenic strategies for cancer therapy.

P53 Gene as a Promising Biomarker and Potential Target for the Early Diagnosis of Reproductive Cancers

One of the crucial aspects of cancer research is diagnosis with specificity and accuracy. Early cancer detection mostly helps make appropriate decisions regarding treatment and metastasis. The well-studied transcription factor tumor suppressor protein p53 is essential for maintaining genetic integrity. p53 is a key tumor suppressor that recognizes the carcinogenic biological pathways and eradicates them by apoptosis. A wide range of carcinomas, especially gynecological such as ovarian, cervical, and endometrial cancers, frequently undergo TP53 gene mutations. This study evaluates the potential of the p53 gene as a biological marker for the diagnosis of reproductive system neoplasms. Immunohistochemistry of p53 is rapid, easy to accomplish, cost-effective, and preferred by pathologists as a surrogate for the analysis of TP53 mutation. Thus, this review lays a groundwork for future efforts to develop techniques using p53 for the early diagnosis of cancer.

Genetic variants associated with weight loss and metabolic outcomes after bariatric surgery: A systematic review

The extent to which genetic variations contribute to interindividual differences in weight loss and metabolic outcomes after bariatric surgery is unknown. Identifying genetic variants that impact surgery outcomes may contribute to clinical decision making. This review evaluates current evidence addressing the association of genetic variants with weight loss and changes in metabolic parameters after bariatric surgery. A search was conducted using Medline, Embase, Scopus, Web of Science, and Cochrane Library. Fifty-two eligible studies were identified. Single nucleotide polymorphisms (SNPs) at ADIPOQ (rs226729, rs1501299, rs3774261, and rs17300539) showed a positive association with postoperative change in measures of glucose homeostasis and lipid profiles (n = 4), but not with weight loss after surgery (n = 6). SNPs at FTO (rs11075986, rs16952482, rs8050136, rs9939609, rs9930506, and rs16945088) (n = 10) and MC4R (rs11152213, rs476828, rs2229616, rs9947255, rs17773430, rs5282087, and rs17782313) (n = 9) were inconsistently associated with weight loss and metabolic improvement. Four studies examining the UCP2 SNP rs660339 reported associations with postsurgical weight loss. In summary, there is limited evidence supporting a role for specific genetic variants in surgical outcomes after bariatric surgery. Most studies have adopted a candidate gene approach, limiting the scope for discovery, suggesting that the absence of compelling evidence is not evidence of absence.

Genetic risk assessment based on association and prediction studies

The genetic basis of phenotypic emergence provides valuable information for assessing individual risk. While association studies have been pivotal in identifying genetic risk factors within a population, complementing it with insights derived from predictions studies that assess individual-level risk offers a more comprehensive approach to understanding phenotypic expression. In this study, we established personalized risk assessment models using single-nucleotide polymorphism (SNP) data from 200 Korean patients, of which 100 experienced hepatitis B surface antigen (HBsAg) seroclearance and 100 patients demonstrated high levels of HBsAg. The risk assessment models determined the predictive power of the following: (1) genome-wide association study (GWAS)-identified candidate biomarkers considered significant in a reference study and (2) machine learning (ML)-identified candidate biomarkers with the highest feature importance scores obtained by using random forest (RF). While utilizing all features yielded 64% model accuracy, using relevant biomarkers achieved higher model accuracies: 82% for 52 GWAS-identified candidate biomarkers, 71% for three GWAS-identified biomarkers, and 80% for 150 ML-identified candidate biomarkers. Findings highlight that the joint contributions of relevant biomarkers significantly influence phenotypic emergence. On the other hand, combining ML-identified candidate biomarkers into the pool of GWAS-identified candidate biomarkers resulted in the improved predictive accuracy of 90%, demonstrating the capability of ML as an auxiliary analysis to GWAS. Furthermore, some of the ML-identified candidate biomarkers were found to be linked with hepatocellular carcinoma (HCC), reinforcing previous claims that HCC can still occur despite the absence of HBsAg.

Gene-based burden scores identify rare variant associations for 28 blood biomarkers

BACKGROUND

A relevant part of the genetic architecture of complex traits is still unknown; despite the discovery of many disease-associated common variants. Polygenic risk score (PRS) models are based on the evaluation of the additive effects attributable to common variants and have been successfully implemented to assess the genetic susceptibility for many phenotypes. In contrast, burden tests are often used to identify an enrichment of rare deleterious variants in specific genes. Both kinds of genetic contributions are typically analyzed independently. Many studies suggest that complex phenotypes are influenced by both low effect common variants and high effect rare deleterious variants. The aim of this paper is to integrate the effect of both common and rare functional variants for a more comprehensive genetic risk modeling.

METHODS

We developed a framework combining gene-based scores based on the enrichment of rare functionally relevant variants with genome-wide PRS based on common variants for association analysis and prediction models. We applied our framework on UK Biobank dataset with genotyping and exome data and considered 28 blood biomarkers levels as target phenotypes. For each biomarker, an association analysis was performed on full cohort using gene-based scores (GBS). The cohort was then split into 3 subsets for PRS construction and feature selection, predictive model training, and independent evaluation, respectively. Prediction models were generated including either PRS, GBS or both (combined).

RESULTS

Association analyses of the cohort were able to detect significant genes that were previously known to be associated with different biomarkers. Interestingly, the analyses also revealed heterogeneous effect sizes and directionality highlighting the complexity of the blood biomarkers regulation. However, the combined models for many biomarkers show little or no improvement in prediction accuracy compared to the PRS models.

CONCLUSION

This study shows that rare variants play an important role in the genetic architecture of complex multifactorial traits such as blood biomarkers. However, while rare deleterious variants play a strong role at an individual level, our results indicate that classical common variant based PRS might be more informative to predict the genetic susceptibility at the population level.

Unified views on variant impact across many diseases

Genomic studies of human disorders are often performed by distinct research communities (i.e., focused on rare diseases, common diseases, or cancer). Despite underlying differences in the mechanistic origin of different disease categories, these studies share the goal of identifying causal genomic events that are critical for the clinical manifestation of the disease phenotype. Moreover, these studies face common challenges, including understanding the complex genetic architecture of the disease, deciphering the impact of variants on multiple scales, and interpreting noncoding mutations. Here, we highlight these challenges in depth and argue that properly addressing them will require a more unified vocabulary and approach across disease communities. Toward this goal, we present a unified perspective on relating variant impact to various genomic disorders.

Evaluating the interactive effects of dietary habits and human gut microbiome on the risks of depression and anxiety

BACKGROUND

Gut microbiome and dietary patterns have been suggested to be associated with depression/anxiety. However, limited effort has been made to explore the effects of possible interactions between diet and microbiome on the risks of depression and anxiety.

METHODS

Using the latest genome-wide association studies findings in gut microbiome and dietary habits, polygenic risk scores (PRSs) analysis of gut microbiome and dietary habits was conducted in the UK Biobank cohort. Logistic/linear regression models were applied for evaluating the associations for gut microbiome-PRS, dietary habits-PRS, and their interactions with depression/anxiety status and Patient Health Questionnaire (PHQ-9)/Generalized Anxiety Disorder-7 (GAD-7) score by R software.

RESULTS

We observed 51 common diet-gut microbiome interactions shared by both PHQ score and depression status, such as overall beef intake × genus Sporobacter [hurdle binary (HB)] (PPHQ = 7.88 × 10-4, Pdepression status = 5.86 × 10-4); carbohydrate × genus Lactococcus (HB) (PPHQ = 0.0295, Pdepression status = 0.0150). We detected 41 common diet-gut microbiome interactions shared by GAD score and anxiety status, such as sugar × genus Parasutterella (rank normal transformed) (PGAD = 5.15 × 10-3, Panxiety status = 0.0347); tablespoons of raw vegetables per day × family Coriobacteriaceae (HB) (PGAD = 6.02 × 10-4, Panxiety status = 0.0345). Some common significant interactions shared by depression and anxiety were identified, such as overall beef intake × genus Sporobacter (HB).

CONCLUSIONS

Our study results expanded our understanding of how to comprehensively consider the relationships for dietary habits-gut microbiome interactions with depression and anxiety.

Genomic Assessment of Cancer Susceptibility in the Threatened Catalina Island Fox (Urocyon littoralis catalinae)

Small effective population sizes raise the probability of extinction by increasing the frequency of potentially deleterious alleles and reducing fitness. However, the extent to which cancers play a role in the fitness reduction of genetically depauperate wildlife populations is unknown. Santa Catalina island foxes (Urocyon littoralis catalinae) sampled in 2007-2008 have a high prevalence of ceruminous gland tumors, which was not detected in the population prior to a recent bottleneck caused by a canine distemper epidemic. The disease appears to be associated with inflammation from chronic ear mite (Otodectes) infections and secondary elevated levels of Staphyloccus pseudointermedius bacterial infections. However, no other environmental factors to date have been found to be associated with elevated cancer risk in this population. Here, we used whole genome sequencing of the case and control individuals from two islands to identify candidate loci associated with cancer based on genetic divergence, nucleotide diversity, allele frequency spectrum, and runs of homozygosity. We identified several candidate loci based on genomic signatures and putative gene functions, suggesting that cancer susceptibility in this population may be polygenic. Due to the efforts of a recovery program and weak fitness effects of late-onset disease, the population size has increased, which may allow selection to be more effective in removing these presumably slightly deleterious alleles. Long-term monitoring of the disease alleles, as well as overall genetic diversity, will provide crucial information for the long-term persistence of this threatened population.

Common genetic variation associated with Mendelian disease severity revealed through cryptic phenotype analysis

Clinical heterogeneity is common in Mendelian disease, but small sample sizes make it difficult to identify specific contributing factors. However, if a disease represents the severely affected extreme of a spectrum of phenotypic variation, then modifier effects may be apparent within a larger subset of the population. Analyses that take advantage of this full spectrum could have substantially increased power. To test this, we developed cryptic phenotype analysis, a model-based approach that infers quantitative traits that capture disease-related phenotypic variability using qualitative symptom data. By applying this approach to 50 Mendelian diseases in two cohorts, we identify traits that reliably quantify disease severity. We then conduct genome-wide association analyses for five of the inferred cryptic phenotypes, uncovering common variation that is predictive of Mendelian disease-related diagnoses and outcomes. Overall, this study highlights the utility of computationally-derived phenotypes and biobank-scale cohorts for investigating the complex genetic architecture of Mendelian diseases.

A wide range of protective and predisposing variants in aggrecan influence the susceptibility for otosclerosis

In this study, we investigated the association of ACAN variants with otosclerosis, a frequent cause of hearing loss among young adults. We sequenced the coding, 5'-UTR and 3'-UTR regions of ACAN in 1497 unrelated otosclerosis cases and 1437 matched controls from six different subpopulations. The association between variants in ACAN and the disease risk was tested through single variant and gene-based association tests. After correction for multiple testing, 14 variants were significantly associated with otosclerosis, ten of which represented independent association signals. Eight variants showed a consistent association across all subpopulations. Allelic odds ratios of the variants identified four predisposing and ten protective variants. Gene-based tests showed an association of very rare variants in the 3'-UTR with the phenotype. The associated exonic variants are all located in the CS domain of ACAN and include both protective and predisposing variants with a broad spectrum of effect sizes and population frequencies. This includes variants with strong effect size and low frequency, typical for monogenic diseases, to low effect size variants with high frequency, characteristic for common complex traits. This single-gene allelic spectrum with both protective and predisposing alleles is unique in the field of complex diseases. In conclusion, these findings are a significant advancement to the understanding of the etiology of otosclerosis.

Advances in colorectal cancer genomics and transcriptomics drive early detection and prevention

Colorectal carcinoma (CRC) is a high incidence cancer and leading cause of cancer mortality worldwide. The advances in genomics and transcriptomics in the past decades have improved the detection and prevention of CRC in familial CRC syndromes. Nevertheless, the ultimate goal of personalized medicine for sporadic CRC is still not within reach due no less to the difficulty in integrating population disparity and clinical data to combat what essentially is a very heterogenous disease. This minireview highlights the achievement of the past decades and present possible direction in the hope of early detection and metastasis prevention for reducing CRC-associated morbidity and mortality.

PopInf: An Approach for Reproducibly Visualizing and Assigning Population Affiliation in Genomic Samples of Uncertain Origin

Germline genetic variation contributes to cancer etiology, but self-reported race is not always consistent with genetic ancestry, and samples may not have identifying ancestry information. In this study, we describe a flexible computational pipeline, PopInf, to visualize principal component analysis output and assign ancestry to samples with unknown genetic ancestry, given a reference population panel of known origins. PopInf is implemented as a reproducible workflow in Snakemake with a tutorial on GitHub. We provide a preprocessed reference population panel that can be quickly and efficiently implemented in cancer genetics studies. We ran PopInf on The Cancer Genome Atlas (TCGA) liver cancer data and identify discrepancies between reported race and inferred genetic ancestry. The PopInf pipeline facilitates visualization and identification of genetic ancestry across samples, so that this ancestry can be accounted for in studies of disease risk.

Interplay Between Autophagy and Wnt/β-Catenin Signaling in Cancer: Therapeutic Potential Through Drug Repositioning

The widespread dysregulation that characterizes cancer cells has been dissected and many regulation pathways common to multiple cancer types have been described in depth. Wnt/β-catenin signaling and autophagy are among these principal pathways, which contribute to tumor growth and resistance to anticancer therapies. Currently, several therapeutic strategies that target either Wnt/β-catenin signaling or autophagy are in various stages of development. Targeted therapies that block specific elements that participate in both pathways; are subject to in vitro studies as well as pre-clinical and early clinical trials. Strikingly, drugs designed for other diseases also impact these pathways, which is relevant since they are already FDA-approved and sometimes even routinely used in the clinic. The main focus of this mini-review is to highlight the importance of drug repositioning to inhibit the Wnt/β-catenin and autophagy pathways, with an emphasis on the interplay between them. The data we found strongly suggested that this field is worth further examination.

Expression, Epigenetic, and Genetic Changes of HNF1B in Colorectal Lesions: an Analysis of 145 Cases

Hepatocyte nuclear factor 1 beta (HNF1B) is transcription factor which plays a crucial role in the regulation of the development of several organs, but also seems to be implicated in the development of certain tumours, especially the subset of clear cell carcinomas of the ovary and kidney. Depending on the type of the tumour, HNF1B may act as either a tumour suppressor or an oncogene, although the exact mechanism by which HNF1B participates in the process of cancerogenesis is unknown. Using immunohistochemical approach and methylation and mutation analysis, we have investigated the expression, epigenetic, and genetic changes of HNF1B on 40 cases of colorectal adenomas and 105 cases of colorectal carcinomas. The expression of HNF1B was correlated with the benign or malignant behaviour of the lesion, given that carcinomas showed significantly lower levels of expression compared to adenomas. In carcinomas, lower levels of HNF1B expression were associated with recurrence and shortened disease-free survival. The mutation analysis revealed three somatic mutations (two frameshift and one nonsense) in the carcinoma sample set. Promoter methylation was detected in three carcinomas. These results suggest that in colorectal cancer, HNF1B may play a part in the pathogenesis and act in a tumour suppressive fashion.

From GWAS to Function: Using Functional Genomics to Identify the Mechanisms Underlying Complex Diseases

Genome-wide association studies (GWAS) have successfully mapped thousands of loci associated with complex traits. These associations could reveal the molecular mechanisms altered in common complex diseases and result in the identification of novel drug targets. However, GWAS have also left a number of outstanding questions. In particular, the majority of disease-associated loci lie in non-coding regions of the genome and, even though they are thought to play a role in gene expression regulation, it is unclear which genes they regulate and in which cell types or physiological contexts this regulation occurs. This has hindered the translation of GWAS findings into clinical interventions. In this review we summarize how these challenges have been addressed over the last decade, with a particular focus on the integration of GWAS results with functional genomics datasets. Firstly, we investigate how the tissues and cell types involved in diseases can be identified using methods that test for enrichment of GWAS variants in genomic annotations. Secondly, we explore how to find the genes regulated by GWAS loci using methods that test for colocalization of GWAS signals with molecular phenotypes such as quantitative trait loci (QTLs). Finally, we highlight potential future research avenues such as integrating GWAS results with single-cell sequencing read-outs, designing functionally informed polygenic risk scores (PRS), and validating disease associated genes using genetic engineering. These tools will be crucial to identify new drug targets for common complex diseases.

The Oncogenic Potential of the Centromeric Border Protein FAM84B of the 8q24.21 Gene Desert

FAM84B is a risk gene in breast and prostate cancers. Its upregulation is associated with poor prognosis of prostate cancer, breast cancer, and esophageal squamous cell carcinoma. FAM84B facilitates cancer cell proliferation and invasion in vitro, and xenograft growth in vivo. The FAM84B and Myc genes border a 1.2 Mb gene desert at 8q24.21. Co-amplification of both occurs in 20 cancer types. Mice deficient of a 430 Kb fragment within the 1.2 Mb gene desert have downregulated FAM84B and Myc expressions concurrent with reduced breast cancer growth. Intriguingly, Myc works in partnership with other oncogenes, including Ras. FAM84B shares similarities with the H-Ras-like suppressor (HRASLS) family over their typical LRAT (lecithin:retinal acyltransferase) domain. This domain contains a catalytic triad, H23, H35, and C113, which constitutes the phospholipase A_1/2 and O-acyltransferase activities of HRASLS1-5. These enzymatic activities underlie their suppression of Ras. FAM84B conserves H23 and H35 but not C113 with both histidine residues residing within a highly conserved motif that FAM84B shares with HRASLS1-5. Deletion of this motif abolishes FAM84B oncogenic activities. These properties suggest a collaboration of FAM84B with Myc, consistent with the role of the gene desert in strengthening Myc functions. Here, we will discuss recent research on FAM84B-derived oncogenic potential.

Challenges in reporting pathogenic/potentially pathogenic variants in 94 cancer predisposing genes - in pediatric patients screened with NGS panels

The benefit of reporting unsolicited findings in Next Generation Sequencing (NGS) related to cancer genes in children may have implications for family members, nevertheless, could also cause distress. We aimed to retrospectively investigate germline variants in 94 genes implicated in oncogenesis, in patients referred to NGS testing for various rare genetic diseases and reevaluate the utility of reporting different classes of pathogenicity. We used in silico prediction software to classify variants and conducted manual review to examine unsolicited findings frequencies in 145 children with rare diseases, that underwent sequencing - using a 4813 gene panel. The anonymized reanalysis revealed 18250 variants, of which 126 were considered after filtering. Six pathogenic variants (in BRCA1,BMPR1A,FANCA,FANCC,NBN genes) with cancer related phenotype and three unsolicited variants (in BRCA2,PALB2,RAD50 genes) were reported to patients. Additionally, three unsolicited variants in ATR, BLM (in two individuals), and FANCB genes presented potential cancer susceptibility, were not reported to patients. In retrospect, 4.8% (7/145) of individuals in our cohort had unsolicited NGS findings related to cancer. More efforts are needed to create an updatable consensus in reporting variants in cancer predisposing genes, especially for children. Consent process is crucial to inform of both value and risk of additional genetic information.

Single nucleotide polymorphisms associated with susceptibility for development of colorectal cancer: Case-control study in a Basque population

Given the significant population diversity in genetic variation, we aimed to investigate whether single nucleotide polymorphisms (SNPs) previously identified in studies of colorectal cancer (CRC) susceptibility were also relevant to the population of the Basque Country (North of Spain). We genotyped 230 CRC cases and 230 healthy controls for 48 previously reported CRC-susceptibility SNPs. Only the rs6687758 in DUPS10 exhibited a statistically significant association with CRC risk based on the crude analysis. The rs6687758 AG genotype conferred about 2.13-fold increased risk for CRC compared to the AA genotype. Moreover, we found significant associations in cases between smoking status, physical activity, and the rs6687758 SNP. The results of a Genetic Risk Score (GRS) showed that the risk alleles were more frequent in cases than controls and the score was associated with CRC in crude analysis. In conclusion, we have confirmed a CRC susceptibility locus and the existence of associations between modifiable factors and the rs6687758 SNP; moreover, the GRS was associated with CRC. However, further experimental validations are needed to establish the role of this SNP, the function of the gene identified, as well as the contribution of the interaction between environmental factors and this locusto the risk of CRC.

Tissue-specific microRNA expression alters cancer susceptibility conferred by a TP53 noncoding variant

A noncoding polymorphism (rs78378222) in TP53, carried by scores of millions of people, was previously associated with moderate risk of brain tumors and other neoplasms. We find a positive association between this variant and soft tissue sarcoma. In sharp contrast, it is protective against breast cancer. We generated a mouse line carrying this variant and found that it accelerates spontaneous tumorigenesis and glioma development, but strikingly, delays mammary tumorigenesis. The variant creates a miR-382-5p targeting site and compromises a miR-325-3p site. Their differential expression results in p53 downregulation in the brain, but p53 upregulation in the mammary gland of polymorphic mice compared to that of wild-type littermates. Thus, this variant is at odds with Li-Fraumeni Syndrome mutants in breast cancer predisposition yet consistent in glioma predisposition. Our findings elucidate an underlying mechanism of cancer susceptibility that is conferred by genetic variation and yet altered by microRNA expression.

Precision medicine in diabetes: an opportunity for clinical translation

Metabolic disorders present a public health challenge of staggering proportions. In diabetes, there is an urgent need to better understand disease heterogeneity, clinical trajectories, and related comorbidities. A pressing and timely question is whether we are ready for precision medicine in diabetes. Some biological insights that have emerged during the last decade have already been used to direct clinical decision making, especially in monogenic forms of diabetes. However, much work is necessary to integrate high-dimensional explorations into complex disease architectures, less penetrant biological alterations, and broader phenotypes, such as type 2 diabetes. In addition, for precision medicine to take hold in diabetes, reproducibility, interpretability, and actionability remain key guiding objectives. In this review, we examine how mounting data sets generated during the last decade to understand biological variability are now inspiring new venues to clarify diabetes nosology and ultimately translate findings into more effective prevention and treatment strategies.

FAM84B promotes prostate tumorigenesis through a network alteration

Background:

The aim of this study was to investigate the contributions of FAM84B in prostate tumorigenesis and progression.

Methods:

A FAM84B mutant with deletion of its HRASLS domain (ΔHRASLS) was constructed. DU145 prostate cancer (PC) cells stably expressing an empty vector (EV), FAM84B, or FAM84B (ΔHRASLS) were produced. These lines were examined for proliferation, invasion, and growth in soft agar in vitro. DU145 EV and FAM84B cells were investigated for tumor growth and lung metastasis in NOD/SCID mice. The transcriptome of DU145 EV xenografts (n = 2) and DU145 FAM84B tumors (n = 2) was determined using RNA sequencing, and analyzed for pathway alterations. The FAM84B-affected network was evaluated for an association with PC recurrence.

Results:

FAM84B but not FAM84B (ΔHRASLS) increased DU145 cell invasion and growth in soft agar. Co-immunoprecipitation and co-localization analyses revealed an interaction between FAM84B and FAM84B (ΔHRASLS), suggesting an intramolecular association among FAM84B molecules. FAM84B significantly enhanced DU145 cell-derived xenografts and lung metastasis. In comparison with DU145 EV cell-produced tumors, those generated by DU145 FAM84B cells showed a large number of differentially expressed genes (DEGs; n = 4976). A total of 51 pathways were enriched in these DEGs, which function in the Golgi-to-endoplasmic reticulum processes, cell cycle checkpoints, mitochondrial events, and protein translation. A novel 27-gene signature (SigFAM) was derived from these DEGs; SigFAM robustly stratifies PC recurrence in two large PC populations (n = 490, p = 0; n = 140, p = 4e⁻¹¹), and remains an independent risk factor of PC recurrence after adjusting for age at diagnosis, Gleason scores, surgical margin, and tumor stages.

Conclusions:

FAM84B promotes prostate tumorigenesis through a complex network that predicts PC recurrence.

INDEX-db: The Indian Exome Reference Database (Phase I)

Deep sequencing-based genetic mapping has greatly enhanced the ability to catalog variants with plausible disease association. Confirming how these identified variants contribute to specific disease conditions, across human populations, poses the next challenge. Differential selection pressure may impact the frequency of genetic variations, and thus detection of association with disease conditions, across populations. To understand genotype to phenotype correlations, it thus becomes important to first understand the spectrum of genetic variation within a population by creating a reference map. In this study, we report the development of phase I of a new database of genetic variations called INDian EXome database (INDEX-db), from the Indian population, with an aim to establish a centralized database of integrated information. This could be useful for researchers involved in studying disease mechanisms at clinical, genetic, and cellular levels.

Metabolic reprogramming of oncogene-addicted cancer cells to OXPHOS as a mechanism of drug resistance

The ability to selectively eradicate oncogene-addicted tumors while reducing systemic toxicity has endeared targeted therapies as a treatment strategy. Nevertheless, development of acquired resistance limits the benefits and durability of such a regime. Here we report evidence of enhanced reliance on mitochondrial oxidative phosphorylation (OXPHOS) in oncogene-addicted cancers manifesting acquired resistance to targeted therapies. To that effect, we describe a novel OXPHOS targeting activity of the small molecule compound, OPB-51602 (OPB). Of note, a priori treatment with OPB restored sensitivity to targeted therapies. Furthermore, cancer cells exhibiting stemness markers also showed selective reliance on OXPHOS and enhanced sensitivity to OPB. Importantly, in a subset of patients who developed secondary resistance to EGFR tyrosine kinase inhibitor (TKI), OPB treatment resulted in decrease in metabolic activity and reduction in tumor size. Collectively, we show here a switch to mitochondrial OXPHOS as a key driver of targeted drug resistance in oncogene-addicted cancers. This metabolic vulnerability is exploited by a novel OXPHOS inhibitor, which also shows promise in the clinical setting.

Penetrance and Expressivity in Inherited Cancer Predisposing Syndromes

Inherited diseases are not always expressed in the same way in every individual that carries the same variant in a disease-causing gene. This phenomenon is known as reduced or incomplete penetrance. Variable and incomplete penetrance may explain why inherited diseases are occasionally transmitted through unaffected parents, but also why clinically healthy individuals can carry potentially pathogenic variants without expressing features of the disease. Here, we will provide an overview of factors that play a fundamental role in the concept of penetrance and expressivity of cancer predisposing genes in children with malignancies. These findings are important to understand the complexity of inherited diseases and cancer development and to improve genetic counselling for the affected families.

Genetic variation affecting exon skipping contributes to brain structural atrophy in Alzheimer's disease

Genetic variation in cis-regulatory elements related to splicing machinery and splicing regulatory elements (SREs) results in exon skipping and undesired protein products. We developed a splicing decision model to identify actionable loci among common SNPs for gene regulation. The splicing decision model identified SNPs affecting exon skipping by analyzing sequence-driven alternative splicing (AS) models and by scanning the genome for the regions with putative SRE motifs. We used non-Hispanic Caucasians with neuroimaging, and fluid biomarkers for Alzheimer's disease (AD) and identified 17,088 common exonic SNPs affecting exon skipping. GWAS identified one SNP (rs1140317) in HLA-DQB1 as significantly associated with entorhinal cortical thickness, AD neuroimaging biomarker, after controlling for multiple testing. Further analysis revealed that rs1140317 was significantly associated with brain amyloid-f deposition (PET and CSF). HLA-DQB1 is an essential immune gene and may regulate AS, thereby contributing to AD pathology. SRE may hold potential as novel therapeutic targets for AD.

Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma

Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway's topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher's exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov-Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level.

MRPL53, a New Candidate Gene for Orofacial Clefting, Identified Using an eQTL Approach

A valuable approach to understand how individual and population genetic differences can predispose to disease is to assess the impact of genetic variants on cellular functions (e.g., gene expression) of cell and tissue types related to pathological states. To understand the genetic basis of nonsyndromic cleft lip with or without cleft palate (NSCL/P) susceptibility, a complex and highly prevalent congenital malformation, we searched for genetic variants with a regulatory role in a disease-related tissue, the lip muscle (orbicularis oris muscle [OOM]), of affected individuals. From 46 OOM samples, which are frequently discarded during routine corrective surgeries on patients with orofacial clefts, we derived mesenchymal stem cells and correlated the individual genetic variants with gene expression from these cultured cells. Through this strategy, we detected significant cis-eQTLs (i.e., DNA variants affecting gene expression) and selected a few candidates to conduct an association study in a large Brazilian cohort (624 patients and 668 controls). This resulted in the discovery of a novel susceptibility locus for NSCL/P, rs1063588, the best eQTL for the MRPL53 gene, where evidence for association was mostly driven by the Native American ancestry component of our Brazilian sample. MRPL53 (2p13.1) encodes a 39S protein subunit of mitochondrial ribosomes and interacts with MYC, a transcription factor required for normal facial morphogenesis. Our study illustrates not only the importance of sampling admixed populations but also the relevance of measuring the functional effects of genetic variants over gene expression to dissect the complexity of disease phenotypes.

Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases

Recently, many new approaches, study designs, and statistical and analytical methods have emerged for studying gene-environment interactions (G×Es) in large-scale studies of human populations. There are opportunities in this field, particularly with respect to the incorporation of -omics and next-generation sequencing data and continual improvement in measures of environmental exposures implicated in complex disease outcomes. In a workshop called "Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases," held October 17-18, 2014, by the National Institute of Environmental Health Sciences and the National Cancer Institute in conjunction with the annual American Society of Human Genetics meeting, participants explored new approaches and tools that have been developed in recent years for G×E discovery. This paper highlights current and critical issues and themes in G×E research that need additional consideration, including the improved data analytical methods, environmental exposure assessment, and incorporation of functional data and annotations.

Cancer is an adaptation that selects in animals against energy dissipation

As cancer usually follows reproduction, it is generally assumed that cancer does not select. Graham has however argued that juvenile cancer, which precedes reproduction, could during evolution have implemented a "cancer selection" that resulted in novel traits that suppress this juvenile cancer; an example is protection against UV sunlight-induced cancer, required for the emergence of terrestrial animals from the sea. We modify the cancer selection mechanism to the posited "cancer adaptation" mechanism, in which juvenile mortality is enhanced through the diminished care received by juveniles from their (grand) parents when these suffer from cancer in old age. Moreover, it is posited that the cancer adaptation selects against germline "dissipative genes", genes that result in enhanced free energy dissipation. Cancer's progression is interpreted as a cascade at increasing scale of repeated amplification of energy dissipation, a cascade involving heat shock, the Warburg effect, the cytokine IL-6, tumours, and hypermetabolism. Disturbance of any physiological process must enhance energy dissipation if the animal remains functioning normally, what explains multicausality, why "everything gives you cancer". The hypothesis thus comprises two newly invoked partial processes-diminished (grand) parental care and dissipation amplification-and results in a "selection against enhanced energy dissipation" which gives during evolution the benefit of energy conservation. Due to this benefit, cancer would essentially be an adaptation, and not a genetic disease, as assumed in the "somatic mutation theory". Cancer by somatic mutations is only a side process. The cancer adaptation hypothesis is substantiated by (1) cancer's extancy, (2) the failure of the somatic mutation theory, (3) cancer's initiation by a high temperature, (4) the interpretation of cancer's progression as a thermal process, and (5) the interpretation of tumours as organs that implement thermogenesis. The hypothesis could in principle be verified by monitoring in a population over several generations (1) the presence of dissipative genes, (2) the incidence of cancer, and (3) the beneficial effect of dissipative gene removal by cancer on starvation/famine survival.

Dihydrotestosterone: Biochemistry, Physiology, and Clinical Implications of Elevated Blood Levels

Benefits associated with lowered serum DHT levels after 5α-reductase inhibitor (5AR-I) therapy in men have contributed to a misconception that circulating DHT levels are an important stimulus for androgenic action in target tissues (e.g., prostate). Yet evidence from clinical studies indicates that intracellular concentrations of androgens (particularly in androgen-sensitive tissues) are essentially independent of circulating levels. To assess the clinical significance of modest elevations in serum DHT and the DHT/testosterone (T) ratio observed in response to common T replacement therapy, a comprehensive review of the published literature was performed to identify relevant data. Although the primary focus of this review is about DHT in men, we also provide a brief overview of DHT in women. The available published data are limited by the lack of large, well-controlled studies of long duration that are sufficiently powered to expose subtle safety signals. Nonetheless, the preponderance of available clinical data indicates that modest elevations in circulating levels of DHT in response to androgen therapy should not be of concern in clinical practice. Elevated DHT has not been associated with increased risk of prostate disease (e.g., cancer or benign hyperplasia) nor does it appear to have any systemic effects on cardiovascular disease safety parameters (including increased risk of polycythemia) beyond those commonly observed with available T preparations. Well-controlled, long-term studies of transdermal DHT preparations have failed to identify safety signals unique to markedly elevated circulating DHT concentrations or signals materially different from T.

Upregulation of FAM84B during prostate cancer progression

Although the FAM84B gene lies within chromosome 8q24, a locus frequently altered in prostate cancer (PC), its alteration during prostate tumorigenesis has not been well studied. We report here FAM84B upregulation in DU145 cell-derived prostate cancer stem-like cells (PCSLCs) and DU145 cell-produced lung metastases compared to subcutaneous xenograft tumors. FAM84B protein was detected in bone metastases and primary PCs. Nanostring examination of 7 pairs of tumor adjacent normal and PC tissues revealed elevations in FAM84B mRNA levels in all carcinomas. Furthermore, through analysis of FAM84B expression using large datasets within the Gene Expression Omnibus and OncomineTM database, we demonstrate significant increases in FAM84B mRNA in 343 primary PCs versus 181 normal tissues, and elevations in the FAM84B gene copy number (GCN) in 171 primary PCs versus 61 normal tissues. While FAM84B was not detected at higher levels via immunohistochemistry in high grade (Gleason score/GS 8-10) tumors compared to GS6-7 PCs, analyses of FAM84B mRNA and GCN using datasets within the cBioPortal database demonstrated FAM84B upregulation in 12% (67/549) of primary PCs and 18% (73/412) of metastatic castration resistant PCs (mCRPCs), and GCN increases in 4.8% (26/546) of primary PCs and 26% (121/467) of mCRPCs, revealing an association of the aforementioned changes with CRPC development. Of note, an increase in FAM84B expression was observed in xenograft CRPCs produced by LNCaP cells. Furthermore, FAM84B upregulation and GCN increases correlate with decreases in disease free survival and overall survival. Collectively, we demonstrate a novel association of FAM84B with PC tumorigenesis and CRPC progression.

Genomics era and complex disorders: Implications of GWAS with special reference to coronary artery disease, type 2 diabetes mellitus, and cancers

The Human Genome Project (HGP) has identified millions of single nucleotide polymorphisms (SNPs) and their association with several diseases, apart from successfully characterizing the Mendelian/monogenic diseases. However, the dissection of precise etiology of complex genetic disorders still poses a challenge for human geneticists. This review outlines the landmark results of genome-wide association studies (GWAS) with respect to major complex diseases - Coronary artery disease (CAD), type 2 diabetes mellitus (T2DM), and predominant cancers. A brief account on the current Indian scenario is also given. All the relevant publications till mid-2015 were accessed through web databases such as PubMed and Google. Several databases providing genetic information related to these diseases were tabulated and in particular, the list of the most significant SNPs identified through GWAS was made, which may be useful for designing studies in functional validation. Post-GWAS implications and emerging concepts such as epigenomics and pharmacogenomics were also discussed.

Receptivity and Preferences for Lifestyle Programs to Reduce Cancer Risk among Lung Cancer Family Members

Background

Lifestyle factors and genetic information has been found to contribute to the occurrence of lung cancer. This study assessed receptivity to participating in lifestyle programs to reduce cancer risk among unaffected lung cancer family members. We also explored demographic, medical, and psychosocial correlates of willingness to participate in lifestyle programs.

Methods

Family members who are part of a lung Cancer Family Registry were asked to fill out a survey assessing their receptivity to cancer risk reduction programs including preferences for an individual or family-based program.

Results

Of the 583 respondents, 85% were “Somewhat” or “Definitely” willing to participate in a lifestyle program. Among those receptive, about half (56%) preferred a family-based approach. Preferred programs included weight management (36%) and nutritional information (30%). Preferred delivery channels were Internet (45%) and mail-based (29%) programs. On multivariate analysis, those definitely/somewhat receptive reported greater exercise self-efficacy scores (p=0.025).

Conclusion

The majority of the sample was receptive to lifestyle programs that might decrease cancer risk. There was a large preference for family-based weight management and nutritional programs. Further research is indicated to determine how to best incorporate a family-based approach to lifestyle programs for cancer family members.

PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions

An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools’ predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2.

Association between APE1 Asp148Glu polymorphism and the risk of urinary cancers: a meta-analysis of 18 case-control studies

Background

Several observational studies suggested that APE1 Asp148Glu was significantly associated with urinary cancers; however, the results of published studies are inconsistent.

Materials and methods

The PubMed and EMBASE were searched for case–control studies regarding the association between Asp148Glu and the risk of urinary cancers with a time limit of September 12, 2015. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the strength of the association between Asp148Glu and the risk of developing prostate cancer, kidney cancer, bladder cancer, as well as all urinary cancers combined.

Results

A total of 18 case–control studies were included in the analysis. Our meta-analysis revealed that the inheritance of at least one APE1 148Glu among Asian men was associated with a 1.26-fold increase in the risk of developing urinary cancers. Meanwhile, APE1 Asp148Glu was significantly associated with the risk of prostate cancer. However, there were no significant relationships between the APE1 SNP (single nucleotide polymorphism) and all urinary cancers combined and bladder cancer and kidney cancer among the men of Caucasian/Asian/African descent or all racial/ethnic groups combined. When stratified by the quality score, no significant association was found in high-quality studies (score ≥7), but a significant increased risk of urinary cancers was observed in lower quality studies (score <7) (dominant model: OR=1.27, 95% CI=1.11–1.45).

Conclusion

Our meta-analysis suggests that APE1 Asp148Glu was not associated with the risk of urinary cancers but might increase the risk of urinary cancers among Asians. Stratification by cancer type identified a significant association of Asp148Glu with prostate cancer.

The mini-driver model of polygenic cancer evolution

Much of cancer genetics research has focused on the identification of the most-important somatic mutations ('major drivers') that cause tumour growth. However, many mutations found in cancer might not be major drivers or 'passenger' mutations, but instead might have relatively weak tumour-promoting effects. Our aim is to highlight the existence of these mutations (termed 'mini drivers' herein), as multiple mini-driver mutations might substitute for a major-driver change, especially in the presence of genomic instability or high mutagen exposure. The mini-driver model has clinical implications: for example, the effects of therapeutically targeting such genes may be limited. However, the main importance of the model lies in helping to provide a complete understanding of tumorigenesis, especially as we anticipate that an increasing number of mini-driver mutations will be found by cancer genome sequencing.

Classification of Cancer Primary Sites Using Machine Learning and Somatic Mutations

An accurate classification of human cancer, including its primary site, is important for better understanding of cancer and effective therapeutic strategies development. The available big data of somatic mutations provides us a great opportunity to investigate cancer classification using machine learning. Here, we explored the patterns of 1,760,846 somatic mutations identified from 230,255 cancer patients along with gene function information using support vector machine. Specifically, we performed a multiclass classification experiment over the 17 tumor sites using the gene symbol, somatic mutation, chromosome, and gene functional pathway as predictors for 6,751 subjects. The performance of the baseline using only gene features is 0.57 in accuracy. It was improved to 0.62 when adding the information of mutation and chromosome. Among the predictable primary tumor sites, the prediction of five primary sites (large intestine, liver, skin, pancreas, and lung) could achieve the performance with more than 0.70 in F-measure. The model of the large intestine ranked the first with 0.87 in F-measure. The results demonstrate that the somatic mutation information is useful for prediction of primary tumor sites with machine learning modeling. To our knowledge, this study is the first investigation of the primary sites classification using machine learning and somatic mutation data.

Gene interference strategies as a new tool for the treatment of prostate cancer

Prostate cancer (PCa) is one of the most common cancer in men. It affects older men and the incidence increases with age; the median age at diagnosis is 67 years. The diagnosis of PCa is essentially based on three tools: digital rectal exam, serum concentration of prostate specific antigen, and transrectal ultrasound-guided biopsy. Currently, the therapeutic treatments of this cancer are different and range from the prostatectomy to hormonal therapy, to radiation therapy, to immunotherapy, and to chemotherapy. However, additional efforts are required in order to find new weapons for the treatment of metastatic setting of disease. The purpose of this review is to highlight new therapeutic strategies based on gene interference; in fact, numerous siRNA and miRNA in the therapeutic treatment of PCa are reported below.

Differential 12-O-Tetradecanoylphorbol-13-acetate-induced activation of rat mammary carcinoma susceptibility Fbxo10 variant promoters via a PKC-AP1 pathway

Rat mammary carcinoma susceptibility 5a1 (Mcs5a1), which is concordant to human MCS5A1 breast cancer risk locus, mediates susceptibility by a non-mammary cell-autonomous mechanism associated with T cell differential expression of F-box protein 10 (Fbxo10). Human FBXO10, an evolutionarily conserved ubiquitin ligase gene, was shown to have a potential role in regulating cell death by controlling the degradation of Bcl-2, a key protein involved in apoptosis. Breast cancer susceptibility is controlled by interactions between environmental and genetic factors; therefore, we sought to determine if breast cancer risk-associated environmental chemicals interact with Mcs5a1 variants using luciferase reporter constructs containing 4.2 kb Fbxo10 promoters based on alleles of mammary cancer susceptible Wistar Furth (WF) and resistant Wistar Kyoto (WKY) rat strains. 12-O-Tetradecanoylphorbol-13-acetate (TPA) induced activation of a 4.2 kb WF Fbxo10 promoter region, but lower levels of activation of the homologous WKY Fbxo10 promoter region. Using general and specific protein kinase inhibitors, we identified a protein kinase C (PKC) pathway that mediated TPA activation. We narrowed the possible PKCs to a member of the atypical PKC isoforms, namely PKCµ. We also determined that activator protein 1 (AP1) family member c-Fos mediated TPA activation of the 4.2 kb WF Fbxo10 promoter. TPA was shown to induce endogenous FBXO10 mRNA and FBXO10 protein in Jurkat cells, a human T cell line, with a maximal level of expression from 1.5 to 2.5 h after exposure. These results indicate that FBXO10/Fbxo10 expression is regulated by a PKC-dependent pathway acting through c-Fos, which binds AP1-specific DNA elements in Mcs5a1.

Allelic variation, aneuploidy, and nongenetic mechanisms suppress a monogenic trait in yeast

Clinically relevant features of monogenic diseases, including severity of symptoms and age of onset, can vary widely in response to environmental differences as well as to the presence of genetic modifiers affecting the trait's penetrance and expressivity. While a better understanding of modifier loci could lead to treatments for Mendelian diseases, the rarity of individuals harboring both a disease-causing allele and a modifying genotype hinders their study in human populations. We examined the genetic architecture of monogenic trait modifiers using a well-characterized yeast model of the human Mendelian disease classic galactosemia. Yeast strains with loss-of-function mutations in the yeast ortholog (GAL7) of the human disease gene (GALT) fail to grow in the presence of even small amounts of galactose due to accumulation of the same toxic intermediates that poison human cells. To isolate and individually genotype large numbers of the very rare (∼0.1%) galactose-tolerant recombinant progeny from a cross between two gal7Δ parents, we developed a new method, called "FACS-QTL." FACS-QTL improves upon the currently used approaches of bulk segregant analysis and extreme QTL mapping by requiring less genome engineering and strain manipulation as well as maintaining individual genotype information. Our results identified multiple distinct solutions by which the monogenic trait could be suppressed, including genetic and nongenetic mechanisms as well as frequent aneuploidy. Taken together, our results imply that the modifiers of monogenic traits are likely to be genetically complex and heterogeneous.

Genetic diversity is a predictor of mortality in humans

BACKGROUND

It has been well-established, both by population genetics theory and direct observation in many organisms, that increased genetic diversity provides a survival advantage. However, given the limitations of both sample size and genome-wide metrics, this hypothesis has not been comprehensively tested in human populations. Moreover, the presence of numerous segregating small effect alleles that influence traits that directly impact health directly raises the question as to whether global measures of genomic variation are themselves associated with human health and disease.

RESULTS

We performed a meta-analysis of 17 cohorts followed prospectively, with a combined sample size of 46,716 individuals, including a total of 15,234 deaths. We find a significant association between increased heterozygosity and survival (P = 0.03). We estimate that within a single population, every standard deviation of heterozygosity an individual has over the mean decreases that person's risk of death by 1.57%.

CONCLUSIONS

This effect was consistent between European and African ancestry cohorts, men and women, and major causes of death (cancer and cardiovascular disease), demonstrating the broad positive impact of genomic diversity on human survival.

Allelic variation, aneuploidy, and nongenetic mechanisms suppress a monogenic trait in yeast

Clinically relevant features of monogenic diseases, including severity of symptoms and age of onset, can vary widely in response to environmental differences as well as to the presence of genetic modifiers affecting the trait’s penetrance and expressivity. While a better understanding of modifier loci could lead to treatments for Mendelian diseases, the rarity of individuals harboring both a disease-causing allele and a modifying genotype hinders their study in human populations. We examined the genetic architecture of monogenic trait modifiers using a well-characterized yeast model of the human Mendelian disease classic galactosemia. Yeast strains with loss-of-function mutations in the yeast ortholog (GAL7) of the human disease gene (GALT) fail to grow in the presence of even small amounts of galactose due to accumulation of the same toxic intermediates that poison human cells. To isolate and individually genotype large numbers of the very rare (∼0.1%) galactose-tolerant recombinant progeny from a cross between two gal7Δ parents, we developed a new method, called “FACS-QTL.” FACS-QTL improves upon the currently used approaches of bulk segregant analysis and extreme QTL mapping by requiring less genome engineering and strain manipulation as well as maintaining individual genotype information. Our results identified multiple distinct solutions by which the monogenic trait could be suppressed, including genetic and nongenetic mechanisms as well as frequent aneuploidy. Taken together, our results imply that the modifiers of monogenic traits are likely to be genetically complex and heterogeneous.