Genomewide scans of complex human diseases: true linkage is hard to find

LUSTR: a new customizable tool for calling genome-wide germline and somatic short tandem repeat variants

BACKGROUND

Short tandem repeats (STRs) are widely distributed across the human genome and are associated with numerous neurological disorders. However, the extent that STRs contribute to disease is likely under-estimated because of the challenges calling these variants in short read next generation sequencing data. Several computational tools have been developed for STR variant calling, but none fully address all of the complexities associated with this variant class.

RESULTS

Here we introduce LUSTR which is designed to address some of the challenges associated with STR variant calling by enabling more flexibility in defining STR loci, allowing for customizable modules to tailor analyses, and expanding the capability to call somatic and multiallelic STR variants. LUSTR is a user-friendly and easily customizable tool for targeted or unbiased genome-wide STR variant screening that can use either predefined or novel genome builds. Using both simulated and real data sets, we demonstrated that LUSTR accurately infers germline and somatic STR expansions in individuals with and without diseases.

CONCLUSIONS

LUSTR offers a powerful and user-friendly approach that allows for the identification of STR variants and can facilitate more comprehensive studies evaluating the role of pathogenic STR variants across human diseases.

Analysis of convergence of linkage and association studies in autism spectrum disorders

Autism spectrum disorder (ASD) is a clinically and genetically heterogeneous group of pervasive neurodevelopmental disorders with a strong hereditary component. Although genome-wide linkage studies (GWLS) and [genome-wide association studies (GWAS)] have previously identified hundreds of ASD risk gene loci, the results remain inconclusive. In this study, a genomic convergence approach of GWAS and GWLS for ASD was implemented for the first time in order to identify genomic loci supported by both methods. A database with 32 GWLS and five GWAS for ASD was created. Convergence was quantified as the proportion of significant GWAS markers located within linked regions. Convergence was not found to be significantly higher than expected by chance (z-test = 1,177, P = 0,239). Although convergence is supportive of genuine effects, the lack of agreement between GWLS and GWAS is also indicative that these studies are designed to answer different questions and are not equally well suited for deciphering the genetics of complex traits.

Genetics, epigenetics, and transcriptomics of preterm birth

Preterm birth contributes significantly to neonatal mortality and morbidity. Despite its global significance, there has only been limited progress in preventing preterm birth. Spontaneous preterm birth (sPTB) results from a wide variety of pathological processes. Although many non-genetic risk factors influence the timing of gestation and labor, compelling evidence supports the role of substantial genetic and epigenetic influences and their interactions with the environment contributing to sPTB. To investigate a common and complex disease such as sPTB, various approaches such as genome-wide association studies, whole-exome sequencing, transcriptomics, and integrative approaches combining these with other 'omics studies have been used. However, many of these studies were typically small or focused on a single ethnicity or geographic region with limited data, particularly in populations at high risk for sPTB, or lacked a robust replication. These studies found many genes involved in the inflammation and immunity-related pathways that may affect sPTB. Recent studies also suggest the role of epigenetic modifications of gene expression by the environmental signals as a potential contributor to the risk of sPTB. Future genetic studies of sPTB should continue to consider the contributions of both maternal and fetal genomes as well as their interaction with the environment.

The Genetic Basis of Moyamoya Disease

Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by progressive spontaneous bilateral occlusion of the intracranial internal cerebral arteries (ICA) and their major branches with compensatory capillary collaterals resembling a “puff of smoke” (Japanese: Moyamoya) on cerebral angiography. These pathological alterations of the vessels are called Moyamoya arteriopathy or vasculopathy and a further distinction is made between primary and secondary MMD. Clinical presentation depends on age and population, with hemorrhage and ischemic infarcts in particular leading to severe neurological dysfunction or even death. Although the diagnostic suspicion can be posed by MRA or CTA, cerebral angiography is mandatory for diagnostic confirmation. Since no therapy to limit the stenotic lesions or the development of a collateral network is available, the only treatment established so far is surgical revascularization. The pathophysiology still remains unknown. Due to the early age of onset, familial cases and the variable incidence rate between different ethnic groups, the focus was put on genetic aspects early on. Several genetic risk loci as well as individual risk genes have been reported; however, few of them could be replicated in independent series. Linkage studies revealed linkage to the 17q25 locus. Multiple studies on the association of SNPs and MMD have been conducted, mainly focussing on the endothelium, smooth muscle cells, cytokines and growth factors. A variant of the RNF213 gene was shown to be strongly associated with MMD with a founder effect in the East Asian population. Although it is unknown how mutations in the RNF213 gene, encoding for a ubiquitously expressed 591 kDa cytosolic protein, lead to clinical features of MMD, RNF213 has been confirmed as a susceptibility gene in several studies with a gene dosage-dependent clinical phenotype, allowing preventive screening and possibly the  development of new therapeutic approaches. This review focuses on the genetic basis of primary MMD only.

Interaction of HULC polymorphisms with Helicobacter pylori infection plays a strong role for the prediction of gastric cancer risk

Aim: Gene-environment interactions have better efficacy in predicting cancer susceptibility than a single gene. Materials & methods: Eight tag single nucleotide polymorphisms encompassing the whole HULC gene were detected by KASP platform (LGC Genomics, Hoddesdon, UK) in 631 gastric cancer (GC) cases and 953 controls. Results: The HULC gene rs7770772 polymorphism could increase GC risk (recessive model: odds ratio = 1.95). The multifactor dimensionality reduction (MDR) analysis suggested that the 2D model HULC rs7770772-Helicobacter pylori had better effect on GC risk prediction (maximum testing accuracy = 0.7005). No significant result was observed in our experimental expression quantitative trait loci analysis. Conclusion: 2D model HULC rs7770772-H. pylori might have superior efficacy for GC risk than a single factor.

Association analysis of vitamin D receptor gene polymorphisms in North England population with Type 2 diabetes mellitus

Background

Numerous diabetes susceptibility loci, include a region consisting vitamin D receptor gene found in chromosome 12q, have been known using genome wide screens.

Aim

The aim of present study is to probe the relationship between polymorphism of vitamin D receptor gene (single nucleotide polymorphisms) and type 2 diabetes mellitus (T2DM). Five hundred T2DM patients and 200 healthy subjects with normal HbA1c (≤ 5.0 %), fasting blood sugar (≤ 120 mg/dL) and random blood sugar (≤ 140 mg/dL) were enrolled.

Metholodgy

The genotypes were found by polymerase chain reaction restriction fragment length polymorphism and DNA sequencing.

Results

revealed that no considerable differences in frequencies of genotype and allele of the Bsm I and Fok I polymorphisms between healthy and patients in the North England (For Fok I: OR = 1.11, 95% CI: 0.72–1.12; for Bsm I: OR = 1.35, 95% CI: 0.79–1.98).

Conclusion

It is recommended that both following polymorphisms of vitamin D receptor gene may not considerably add to the progression of T2DM in the North England.

Targeted Gene Candidates for Treatment and Early Diagnosis of Age-Related Macular Degeneration

Age-related macular degeneration (AMD) is an eye disease that impairs the sharp and central vision need for daily activities. Recent advances in molecular biology research not only lead to a better understanding of the genetics and pathophysiology of AMD but also to the development of applications based on targeted gene expressions to treat the disease. Clarification of molecular pathways that causing to development and progression in dry and wet types of AMD needs comprehensive and comparative investigations in particular precious biopsies involving peripheral blood samples from the patients. Therefore, in this investigation, dry and wet types of AMD patients and healthy individuals were aimed at investigating in regard to targeted gene candidates by using gene expression analysis for the first time. 13 most potent candidate genes involved in neurodegeneration were selected via in silico approach and investigated through gene expression analysis to suggest new targets for disease therapy. For the analyses, 30 individuals (10 dry and 10 wet types AMD patients and 10 healthy people) were involved in the study. SYBR-Green based Real-Time PCR analysis was performed on isolated peripheral blood mononuclear cells (PBMCs) to analyze differentially expressed genes related to these cases. According to the investigations, only the CRP gene was found to be upregulated for both dry and wet disease types. When the downregulated genes were analyzed, it was found that 11 genes were commonly decreased for both dry and wet types in the aspect of expression pattern. From these genes, CFH, CX3CR1, FLT1, and TIMP3 were found to have the most downregulated gene expression properties for both diseases. From these results, it might be concluded that these common upregulated and downregulated genes could be used as targets for early diagnosis and treatment for AMD.

Genetic test for the prescription of diets in support of physical activity

Owing to the fields of nutrigenetics and nutrigenomics today we can think of devising approaches to optimize health, delay onset of diseases and reduce its severity according to our genetic blue print. However this requires a deep understanding of nutritional impact on expression of genes that may result in a specific phenotype. The extensive research and observational studies during last two decades reporting interactions between genes, diet and physical activity suggest a cross talk between various genetic and environmental factors and lifestyle interventions. Although considerable efforts have been made in unraveling the mechanisms of gene-diet interactions the scientific evidences behind developing commercial genetic tests for providing personalized nutrition recommendations are still scarce. In this scenario the current mini-review aims to provide useful insights into salient feature of nutrition based genetic research and its commercial application and the ethical issue and concerns related to its outcome.

Genotypes and Phenotypes: A Search for Influential Genes in Diabetic Retinopathy

Although gene–environment interactions are known to play an important role in the inheritance of complex traits, it is still unknown how a genotype and the environmental factors result in an observable phenotype. Understanding this complex interaction in the pathogenesis of diabetic retinopathy (DR) remains a big challenge as DR appears to be a disease with heterogenous phenotypes with multifactorial influence. In this review, we examine the natural history and risk factors related to DR, emphasizing distinct clinical phenotypes and their natural course in retinopathy. Although there is strong evidence that duration of diabetes and metabolic factors play a key role in the pathogenesis of DR, accumulating new clinical studies reveal that this disease can develop independently of duration of diabetes and metabolic dysfunction. More recently, studies have emphasized the role of genetic factors in DR. However, linkage analyses, candidate gene studies, and genome-wide association studies (GWAS) have not produced any statistically significant results. Our recently initiated genomics study, the Diabetic Retinopathy Genomics (DRGen) Study, aims to examine the contribution of rare and common variants in the development DR, and how they can contribute to clinical phenotype, rate of progression, and response to available therapies. Our preliminary findings reveal a novel set of genetic variants associated with proangiogenic and inflammatory pathways that may contribute to DR pathogenesis. Further investigation of these variants is necessary and may lead to development of novel biomarkers and new therapeutic targets in DR.

Genetic variants affecting bone mineral density and bone mineral content at multiple skeletal sites in Hispanic children

CONTEXT

Osteoporosis is a major public health burden with significant economic costs. However, the correlates of bone health in Hispanic children are understudied.

OBJECTIVE

We aimed to identify genetic variants associated with bone mineral density (BMD) and bone mineral content (BMC) at multiple skeletal sites in Hispanic children.

METHODS

We conducted a cross-sectional genome-wide linkage analysis, genome-wide and exome-wide association analysis of BMD and BMC. The Viva La Familia Study is a family-based cohort with a total of 1030 Hispanic children (4-19 years old at baseline) conducted in Houston, TX. BMD and BMC were measured by Dual-energy X-ray absorptiometry.

RESULTS

Significant heritability were observed for BMC and BMD at multiple skeletal sites ranging between 44 and 68% (P < 2.8 × 10-9). Significant evidence for linkage was found for BMD of pelvis and left leg on chromosome 7p14, lumbar spine on 20q13 and left rib on 6p21, and BMC of pelvis on chromosome 20q12 and total body on 14q22-23 (logarithm of odds score > 3). We found genome-wide significant association between BMC of right arm and rs762920 at PVALB (P = 4.6 × 10-8), and between pelvis BMD and rs7000615 at PTK2B (P = 7.4 × 10-8). Exome-wide association analysis revealed novel association of variants at MEGF10 and ABRAXAS2 with left arm and lumber spine BMC, respectively (P < 9 × 10-7).

CONCLUSIONS

We identified novel loci associated with BMC and BMD in Hispanic children, with strongest evidence for PTK2B. These findings provide better understanding of bone genetics and shed light on biological mechanisms underlying BMD and BMC variation.

Machine learning analysis of exome trios to contrast the genomic architecture of autism and schizophrenia

BACKGROUND

Machine learning (ML) algorithms and methods offer great tools to analyze large complex genomic datasets. Our goal was to compare the genomic architecture of schizophrenia (SCZ) and autism spectrum disorder (ASD) using ML.

METHODS

In this paper, we used regularized gradient boosted machines to analyze whole-exome sequencing (WES) data from individuals SCZ and ASD in order to identify important distinguishing genetic features. We further demonstrated a method of gene clustering to highlight which subsets of genes identified by the ML algorithm are mutated concurrently in affected individuals and are central to each disease (i.e., ASD vs. SCZ "hub" genes).

RESULTS

In summary, after correcting for population structure, we found that SCZ and ASD cases could be successfully separated based on genetic information, with 86-88% accuracy on the testing dataset. Through bioinformatic analysis, we explored if combinations of genes concurrently mutated in patients with the same condition ("hub" genes) belong to specific pathways. Several themes were found to be associated with ASD, including calcium ion transmembrane transport, immune system/inflammation, synapse organization, and retinoid metabolic process. Moreover, ion transmembrane transport, neurotransmitter transport, and microtubule/cytoskeleton processes were highlighted for SCZ.

CONCLUSIONS

Our manuscript introduces a novel comparative approach for studying the genetic architecture of genetically related diseases with complex inheritance and highlights genetic similarities and differences between ASD and SCZ.

Do Genomic Factors Play a Role in Diabetic Retinopathy?

Although there is strong clinical evidence that the control of blood glucose, blood pressure, and lipid level can prevent and slow down the progression of diabetic retinopathy (DR) as shown by landmark clinical trials, it has been shown that these factors only account for 10% of the risk for developing this disease. This suggests that other factors, such as genetics, may play a role in the development and progression of DR. Clinical evidence shows that some diabetics, despite the long duration of their diabetes (25 years or more) do not show any sign of DR or show minimal non-proliferative diabetic retinopathy (NPDR). Similarly, not all diabetics develop proliferative diabetic retinopathy (PDR). So far, linkage analysis, candidate gene studies, and genome-wide association studies (GWAS) have not produced any statistically significant results. We recently initiated a genomics study, the Diabetic Retinopathy Genetics (DRGen) Study, to examine the contribution of rare and common variants in the development of different phenotypes of DR, as well as their responsiveness to anti-VEGF treatment in diabetic macular edema (DME). Our preliminary findings reveal a novel set of genetic variants involved in the angiogenesis and inflammatory pathways that contribute to DR progression or protection. Further investigation of variants can help to develop novel biomarkers and lead to new therapeutic targets in DR.

HS-MMGKG: A Fast Multi-objective Harmony Search Algorithm for Two-locus Model Detection in GWAS

Background::

Genome-Wide Association Study (GWAS) plays a very important role in identifying the causes of a disease. Because most of the existing methods for genetic-interaction detection in GWAS are designed for a single-correlation model, their performances vary considerably for different disease models. These methods usually have high computation cost and low accuracy.

Method::

We present a new multi-objective heuristic optimization methodology named HSMMGKG for detecting genetic interactions. In HS-MMGKG, we use harmony search with five objective functions to improve the efficiency and accuracy. A new strategy based on p-value and MDR is adopted to generate more reasonable results. The Boolean representation in BOOST is modified to calculate the five functions rapidly. These strategies take less time complexity and have higher accuracy while detecting the potential models.

Results::

We compared HS-MMGKG with CSE, MACOED and FHSA-SED using 26 simulated datasets. The experimental results demonstrate that our method outperforms others in accuracy and computation time. Our method has identified many two-locus SNP combinations that are associated with seven diseases in WTCCC dataset. Some of the SNPs have direct evidence in CTD database. The results may be helpful to further explain the pathogenesis.

Conclusion::

It is anticipated that our proposed algorithm could be used in GWAS which is helpful in understanding disease mechanism, diagnosis and prognosis.

Association between MSX1 rs12532 polymorphism with nonsyndromic unilateral complete cleft lip and palate and tooth agenesis

OBJECTIVES

To investigate the association of MSX1 rs12532 polymorphism with the risk of nonsyndromic unilateral complete cleft lip and palate (NSCLP) and tooth agenesis.

MATERIALS AND METHODS

The study is comprised of 384 individuals divided into 4 groups: group 1, patients with unilateral complete NSCLP and premolar agenesis (n = 57); group 2, patients with unilateral NSCLP without tooth agenesis (n = 117); group 3, patients with premolar agenesis without oral cleft (n = 53) and group 4 (n = 157), a control group with individuals without tooth agenesis and oral cleft. Genotyping of rs12532 was carried out with Taqman chemistry, and associations were investigated using logistic regression analyses.

RESULTS

Overall rs12532 allele and genotype distributions revealed no significant differences between the groups of NSCLP or tooth agenesis.

CONCLUSION

Although our results are consistent with a lack of association of MSX1 rs12532 and the risk of unilateral NSCLP and tooth agenesis, further studies with additional SNPs and a more diverse ethnic cohort are warranted.

Genetics and the heart rate response to exercise

The acute heart rate response to exercise, i.e., heart rate increase during and heart rate recovery after exercise, has often been associated with all-cause and cardiovascular mortality. The long-term response of heart rate to exercise results in favourable changes in chronotropic function, including decreased resting and submaximal heart rate as well as increased heart rate recovery. Both the acute and long-term heart rate response to exercise have been shown to be heritable. Advances in genetic analysis enable researchers to investigate this hereditary component to gain insights in possible molecular mechanisms underlying interindividual differences in the heart rate response to exercise. In this review, we comprehensively searched candidate gene, linkage, and genome-wide association studies that investigated the heart rate response to exercise. A total of ten genes were associated with the acute heart rate response to exercise in candidate gene studies. Only one gene (CHRM2), related to heart rate recovery, was replicated in recent genome-wide association studies (GWASs). Additional 17 candidate causal genes were identified for heart rate increase and 26 for heart rate recovery in these GWASs. Nine of these genes were associated with both acute increase and recovery of the heart rate during exercise. These genes can be broadly categorized into four categories: (1) development of the nervous system (CCDC141, PAX2, SOX5, and CAV2); (2) prolongation of neuronal life span (SYT10); (3) cardiac development (RNF220 and MCTP2); (4) cardiac rhythm (SCN10A and RGS6). Additional 10 genes were linked to long-term modification of the heart rate response to exercise, nine with heart rate increase and one with heart rate recovery. Follow-up will be essential to get functional insights in how candidate causal genes affect the heart rate response to exercise. Future work will be required to translate these findings to preventive and therapeutic applications.

Genetic Factors Associated With Human Physical Activity: Are Your Genes Too Tight To Prevent You Exercising?

The benefits of physical activity (PA) on health and fitness are well known. It has become apparent from studies of heritability that there is a considerable genetic component to PA. However, PA is such a complex phenotype that the measurement and quantification of it provide a challenge to a clearer understanding of its genetic basis. In this review, we assessed available evidence from family and twin studies that have estimated the heritability of PA. Heritability is greater when evaluated by accelerometry compared with questionnaires, and for questionnaires higher in twin than family studies. Accelerometry studies suggest heritability of PA is 51% to 56%. There have been many genome-wide linkage studies, candidate gene studies, and four genome-wide association studies that have highlighted specific genetic factors linked to different PA levels. These studies have generally failed to replicate identified loci, with the exception of the melanocortin 4 receptor, and this may be because of the variability in the measurement techniques used to characterize the behavior. Future work should aim to standardize the procedures used to measure PA in the context of trying to identify genetic causes. The link of genetics to physical exercise is not so tight that it prevents voluntary interventions.

Machine learning in schizophrenia genomics, a case-control study using 5,090 exomes

Our hypothesis is that machine learning (ML) analysis of whole exome sequencing (WES) data can be used to identify individuals at high risk for schizophrenia (SCZ). This study applies ML to WES data from 2,545 individuals with SCZ and 2,545 unaffected individuals, accessed via the database of genotypes and phenotypes (dbGaP). Single nucleotide variants and small insertions and deletions were annotated by ANNOVAR using the reference genome hg19/GRCh37. Rare (predicted functional) variants with a minor allele frequency ≤1% and genotype quality ≥90 including missense, frameshift, stop gain, stop loss, intronic, and exonic splicing variants were selected. A file containing all cases and controls, the names of genes with variants meeting our criteria, and the number of variants per gene for each individual, was used for ML analysis. The supervised machine-learning algorithm used the patterns of variants observed in the different genes to determine which subset of genes can best predict that an individual is affected. Seventy percent of the data was used to train the algorithm and the remaining 30% of data (n = 1,526) was used to evaluate its efficiency. The supervised ML algorithm, gradient boosted trees with regularization (eXtreme Gradient Boosting implementation) was the best performing algorithm yielding promising results (accuracy: 85.7%, specificity: 86.6%, sensitivity: 84.9%, area under the receiver-operator characteristic curve: 0.95). The top 50 features (genes) of the algorithm were analyzed using bioinformatics resources for new insights about the pathophysiology of SCZ. This manuscript presents a novel predictor which could potentially enable studies exploring disease-modifying intervention in the early stages of the disease.

Established and emerging strategies to crack the genetic code of obesity

Tremendous progress has been made in the genetic elucidation of obesity over the past two decades, driven largely by technological, methodological and organizational innovations. Current strategies for identifying obesity-predisposing loci/genes, including cytogenetics, linkage analysis, homozygosity mapping, admixture mapping, candidate gene studies, genome-wide association studies, custom genotyping arrays, whole-exome sequencing and targeted exome sequencing, have achieved differing levels of success, and the identified loci in aggregate explain only a modest fraction of the estimated heritability of obesity. This review outlines the successes and limitations of these approaches and proposes novel strategies, including the use of exceptionally large sample sizes, the study of diverse ethnic groups and deep phenotypes and the application of innovative methods and study designs, to identify the remaining obesity-predisposing genes. The use of both established and emerging strategies has the potential to crack the genetic code of obesity in the not-too-distant future. The resulting knowledge is likely to yield improvements in obesity prediction, prevention and care.

Exploring rare and low-frequency variants in the Saguenay-Lac-Saint-Jean population identified genes associated with asthma and allergy traits

The Saguenay–Lac-Saint-Jean (SLSJ) region is located in northeastern Quebec and is known for its unique demographic history and founder effect. As founder populations are enriched with population-specific variants, we characterized the variants distribution in SLSJ and compared it with four European populations (Finnish, Sweden, United Kingdom and France), of which the Finnish population is another founder population. Targeted sequencing of the coding and non-coding immune regulatory regions of the SLSJ asthma familial cohort and the four European populations were performed. Rare and low-frequency coding and non-coding regulatory variants identified in the SLSJ population were then investigated for variant- and gene-level associations with asthma and allergy-related traits (eosinophil percentage, immunoglobulin (Ig) E levels and lung function). Our data showed that (1) rare or deleterious variants were not enriched in the two founder populations as compared with the three non-founder European populations; (2) a larger proportion of founder population-specific variants occurred with higher frequencies; and (3) low-frequency variants appeared to be more deleterious. Furthermore, a rare variant, rs1386931, located in the 3ʹ-UTR of CXCR6 and intron of FYCO1 was found to be associated with eosinophil percentage. Gene-based analyses identified NRP2, MRPL44 and SERPINE2 to be associated with various asthma and allergy-related traits. Our study demonstrated the usefulness of using a founder population to identify new genes associated with asthma and allergy-related traits; thus better understand the genes and pathways implicated in pathophysiology.

SNP-SNP interactions of three new pri-miRNAs with the target gene PGC and multidimensional analysis of H. pylori in the gastric cancer/atrophic gastritis risk in a Chinese population

Gastric cancer (GC) is a multistep complex disease involving multiple genes, and gene–gene interactions have a greater effect than a single gene in determining cancer susceptibility. This study aimed to explore the interaction of the let-7e rs8111742, miR-365b rs121224, and miR-4795 rs1002765 single nucleotide polymorphisms (SNPs) with SNPs of the predicted target gene PGC and Helicobacter pylori status in GC and atrophic gastritis (AG) risk. Three miRNA SNPs and seven PGC SNPs were detected in 2448 cases using the Sequenom MassArray platform. Two pairwise combinations of miRNA and PGC SNPs were associated with increased AG risk (let-7e rs8111742 – PGC rs6458238 and miR-4795 rs1002765 – PGC rs9471643). Singly, miR-365b rs121224 and PGC rs6912200 had no effect individually but in combination they demonstrated an epistatic interaction associated with AG risk. Similarly, let-7e rs8111742 and miR-4795 rs1002765 SNPs interacted with H. pylori infection to increase GC risk (rs8111742: P_interaction = 0.024; rs1002765: P_interaction = 0.031, respectively). A three-dimensional interaction analysis found miR-4795 rs1002765, PGC rs9471643, and H. pylori infection positively interacted to increase AG risk (P_{interaction =} 0.027). Also, let-7e rs8111742, PGC rs6458238, and H. pylori infection positively interacted to increase GC risk (P_{interaction =} 0.036). Furthermore, both of these three-dimensional interactions had a dosage–effect correspondence (P_trend < 0.001) and were verified by MDR. In conclusion, the miRNAs SNPs (let-7e rs8111742 and miR-4795 rs1002765) might have more superior efficiency when combined with PGC SNPs and/or H. pylori for GC or AG risk than a single SNP on its own.

The genetics of obstructive sleep apnoea

Obstructive sleep apnoea (OSA) is a common chronic disease and is associated with high social and economic costs. OSA is heritable, and there is evidence of both direct genetic contributions to OSA susceptibility and indirect contributions via 'intermediate' phenotypes such as obesity, craniofacial structure, neurological control of upper airway muscles and of sleep and circadian rhythm. Investigation of the genetics of OSA is an important research area and may lead to improved understanding of disease aetiology, pathogenesis, adverse health consequences and new preventive strategies and treatments. Genetic studies of OSA have lagged behind other chronic diseases; however recent gene discovery efforts have been successful in finding genetic loci contributing to OSA-associated intermediate phenotypes. Nevertheless, many of the seminal questions relating to the genetic epidemiology of OSA and associated factors remain unanswered. This paper reviews the current state of knowledge of the genetics of OSA, with a focus on genomic approaches to understanding sleep apnoea.

Family studies to find rare high risk variants in migraine

INTRODUCTION

Migraine has long been known as a common complex disease caused by genetic and environmental factors. The pathophysiology and the specific genetic susceptibility are poorly understood. Common variants only explain a small part of the heritability of migraine. It is thought that rare genetic variants with bigger effect size may be involved in the disease. Since migraine has a tendency to cluster in families, a family approach might be the way to find these variants. This is also indicated by identification of migraine-associated loci in classical linkage-analyses in migraine families. A single migraine study using a candidate-gene approach was performed in 2010 identifying a rare mutation in the TRESK potassium channel segregating in a large family with migraine with aura, but this finding has later become questioned. The technologies of next-generation sequencing (NGS) now provides an affordable tool to investigate the genetic variation in the entire exome or genome. The family-based study design using NGS is described in this paper. We also review family studies using NGS that have been successful in finding rare variants in other common complex diseases in order to argue the promising application of a family approach to migraine.

METHOD

PubMed was searched to find studies that looked for rare genetic variants in common complex diseases through a family-based design using NGS, excluding studies looking for de-novo mutations, or using a candidate-gene approach and studies on cancer. All issues from Nature Genetics and PLOS genetics 2014, 2015 and 2016 (UTAI June) were screened for relevant papers. Reference lists from included and other relevant papers were also searched. For the description of the family-based study design using NGS an in-house protocol was used.

RESULTS

Thirty-two successful studies, which covered 16 different common complex diseases, were included in this paper. We also found a single migraine study. Twenty-three studies found one or a few family specific variants (less than five), while other studies found several possible variants. Not all of them were genome wide significant. Four studies performed follow-up analyses in unrelated cases and controls and calculated odds ratios that supported an association between detected variants and risk of disease. Studies of 11 diseases identified rare variants that segregated fully or to a large degree with the disease in the pedigrees.

CONCLUSION

It is possible to find rare high risk variants for common complex diseases through a family-based approach. One study using a family approach and NGS to find rare variants in migraine has already been published but with strong limitations. More studies are under way.

The Genetics of Physical Activity

PURPOSE OF REVIEW

Physical activity (PA) is a well-established modifiable lifestyle determinant for multiple cardio-metabolic outcomes. While many psychosocial and environmental correlates of PA have been identified, current understanding of the genetic architecture that contributes to PA is still very limited, especially when compared to other phenotypes such as obesity and diabetes.

RECENT FINDINGS

This review systematically and comprehensively assesses available evidence from animal experiments, family studies, population-based candidate gene analyses, and genome-wide association studies (GWAS) studying the genetics of physical activity patterns. It discusses the scientific evolution in the field of PA genetics, including the recognition of increased sample sizes, the shift from early family-based approaches to association-based design, and the rapidly advancement of enabling genotyping and sequencing technologies. In addition, this review points to the gaps in the current knowledge base, including the general lack of GWAS and whole-genome sequence analyses particularly understudied populations, and the need for large-scale collaborative effort in both observational and experimental settings. In this review, we also call for research utilizing systems biology strategies for PA genetic research and accounting for complex gene-environment interactions that may vary by race/ethnicity. The epidemic of physical inactivity has been a public health nemesis, encompassing a large burden of diseases and high societal costs. A better understanding of the genetic basis of PA can inform public health policies for the prevention, control, and treatment of many chronic diseases related to physical inactivity.

Molecular Aspects of Wound Healing and the Rise of Venous Leg Ulceration: Omics Approaches to Enhance Knowledge and Aid Diagnostic Discovery

Chronic wounds, in particular venous leg ulcers (VLU), represent a substantial burden for economies, healthcare systems and societies worldwide. This burden is exacerbated by the recalcitrant nature of these wounds, despite best practice, evidence-based care, which substantially reduces the quality of life of patients. Furthermore, co-morbidities such as diabetes and cardiovascular disease within ageing populations further contribute to the increasing prevalence in developed countries. This review provides an overview of the literature concerning the cellular and molecular mechanisms of wound healing and aspects where this process fails, resulting in a chronic wound. VLU may arise from chronic venous disease, which presents with many clinical manifestations and can lead to a highly complex disease state. Efforts to comprehend this state using various omics based approaches have delivered some insight into the underlying biology of chronic wounds and revealed markers of differentiation at the genomic, transcriptomic, proteomic and metabolomic levels. Furthermore, this review outlines the array of analytical tools and approaches that have been utilised for capturing multivariate data at each of these molecular levels. Future developments in spatiotemporal analysis of wounds along with the integration of multiple omics datasets may provide much needed information on the key molecules that drive wound chronicity. Such biomarkers have the potential to be developed into clinically relevant diagnostic tools to aid in personalised wound management.

Design Considerations for Genetic Linkage and Association Studies

This chapter describes the main issues that genetic epidemiologists usually consider in the design of linkage and association studies. For linkage, we briefly consider the situation of rare highly penetrant alleles showing a disease pattern consistent with Mendelian inheritance investigated through parametric methods in large pedigrees, or with autozygosity mapping in inbred families, and we then turn our focus to the most common design, the affected sibling pair design that is of more relevance for common, complex diseases. Power and sample size calculations are provided as a function of the strength of the genetic effect being investigated. We also discuss the impact of other determinants of statistical power such as disease heterogeneity, pedigree and genotyping errors and the effect of the type and density of genetic markers. For association studies, we consider the popular case-control design for dichotomous phenotypes and we provide power and sample size calculations for one-stage and multistage designs. For candidate genes, guidelines are given on the prioritization of genetic variants, and for genome-wide association studies (GWAS) the issue of choosing an appropriate SNP array is discussed. A warning is issued regarding the danger of designing an underpowered replication study following an initial GWAS. The risk of finding spurious association due to population stratification, cryptic relatedness, and differential bias is underlined.

Genetic markers: Potential candidates for cardiovascular disease

The effective prevention of cardiovascular disease depends upon the ability to recognize the high-risk individuals at an early stage of the disease or long before the development of adverse events. Evolving technologies in the fields of proteomics, metabolomics, and genomics have played a significant role in the discovery of cardiovascular biomarkers, but so far these methods have achieved the modest success. Hence, there is a crucial need for more reliable, suitable, and lasting diagnostic and therapeutic markers to screen the disease well in time to start the clinical aid to the patients. Gene polymorphisms associated with the cardiovascular disease play a decisive role in the disease onset. Therefore, the genetic marker evaluation to classify high-risk patients from low-risk patients trends an effective approach to patient management and care. Currently, there are no genetic markers available for extensive adoption as risk factors for coronary vascular disease, yet, there are numerous promising, biologically acceptable candidates. Many of these gene biomarkers, alone or in combination, can play an essential role in the prediction of cardiovascular risk. The present review highlights some putative emerging genetic biomarkers that could facilitate more authentic and fast diagnosis of CVD. This review also briefly describes few technological approaches employed in the biomarker search.

GenomeRunner web server: regulatory similarity and differences define the functional impact of SNP sets

MOTIVATION

The growing amount of regulatory data from the ENCODE, Roadmap Epigenomics and other consortia provides a wealth of opportunities to investigate the functional impact of single nucleotide polymorphisms (SNPs). Yet, given the large number of regulatory datasets, researchers are posed with a challenge of how to efficiently utilize them to interpret the functional impact of SNP sets.

RESULTS

We developed the GenomeRunner web server to automate systematic statistical analysis of SNP sets within a regulatory context. Besides defining the functional impact of SNP sets, GenomeRunner implements novel regulatory similarity/differential analyses, and cell type-specific regulatory enrichment analysis. Validated against literature- and disease ontology-based approaches, analysis of 39 disease/trait-associated SNP sets demonstrated that the functional impact of SNP sets corresponds to known disease relationships. We identified a group of autoimmune diseases with SNPs distinctly enriched in the enhancers of T helper cell subpopulations, and demonstrated relevant cell type-specificity of the functional impact of other SNP sets. In summary, we show how systematic analysis of genomic data within a regulatory context can help interpreting the functional impact of SNP sets.

AVAILABILITY AND IMPLEMENTATION

GenomeRunner web server is freely available at http://www.integrativegenomics.org/

CONTACT

mikhail.dozmorov@gmail.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

DNA methylation in endometriosis (Review)

Endometriosis is defined by the presence and growth of functional endometrial tissue, outside the uterine cavity, primarily in the ovaries, pelvic peritoneum and rectovaginal septum. Although it is a benign disease, it presents with malignant characteristics, such as invasion to surrounding tissues, metastasis to distant locations and recurrence following treatment. Accumulating evidence suggests that various epigenetic aberrations may play an essential role in the pathogenesis of endometriosis. Aberrant DNA methylation represents a possible mechanism repsonsible for this disease, linking gene expression alterations observed in endometriosis with hormonal and environmental factors. Several lines of evidence indicate that endometriosis may partially be due to selective epigenetic deregulations influenced by extrinsic factors. Previous studies have shed light into the epigenetic component of endometriosis, reporting variations in the epigenetic patterns of genes known to be involved in the aberrant hormonal, immunologic and inflammatory status of endometriosis. Although recent studies, utilizing advanced molecular techniques, have allowed us to further elucidate the possible association of DNA methylation with altered gene expression, whether these molecular changes represent the cause or merely the consequence of the disease is a question which remains to be answered. This review provides an overview of the current literature on the role of DNA methylation in the pathophysiology and malignant evolution of endometriosis. We also provide insight into the mechanisms through which DNA methylation-modifying agents may be the next step in the research of the pharmaceutical treatment of endometriosis.

Age-related macular degeneration: Complement in action

The complement system plays a key role in host-defense against common pathogens but must be tightly controlled to avoid inflammation and tissue damage. Polymorphisms in genes encoding two important negative regulators of the alternative complement pathway, complement factor H (CFH) and complement factor I (CFI), are associated with the risk for Age-Related Macular Degeneration (AMD), a leading cause of vision impairment in the ageing population. In this review, we will discuss the genetic basis of AMD and the potential impact of complement de-regulation on disease pathogenesis. Finally, we will highlight recent therapeutic approaches aimed at controlling complement activation in patients with AMD.

HPMV: human protein mutation viewer - relating sequence mutations to protein sequence architecture and function changes

Next-generation sequencing advances are rapidly expanding the number of human mutations to be analyzed for causative roles in genetic disorders. Our Human Protein Mutation Viewer (HPMV) is intended to explore the biomolecular mechanistic significance of non-synonymous human mutations in protein-coding genomic regions. The tool helps to assess whether protein mutations affect the occurrence of sequence-architectural features (globular domains, targeting signals, post-translational modification sites, etc.). As input, HPMV accepts protein mutations - as UniProt accessions with mutations (e.g. HGVS nomenclature), genome coordinates, or FASTA sequences. As output, HPMV provides an interactive cartoon showing the mutations in relation to elements of the sequence architecture. A large variety of protein sequence architectural features were selected for their particular relevance to mutation interpretation. Clicking a sequence feature in the cartoon expands a tree view of additional information including multiple sequence alignments of conserved domains and a simple 3D viewer mapping the mutation to known PDB structures, if available. The cartoon is also correlated with a multiple sequence alignment of similar sequences from other organisms. In cases where a mutation is likely to have a straightforward interpretation (e.g. a point mutation disrupting a well-understood targeting signal), this interpretation is suggested. The interactive cartoon can be downloaded as standalone viewer in Java jar format to be saved and viewed later with only a standard Java runtime environment. The HPMV website is: http://hpmv.bii.a-star.edu.sg/ .

Leveraging Epidemiologic and Clinical Collections for Genomic Studies of Complex Traits

BACKGROUND/AIMS

Present-day limited resources demand DNA and phenotyping alternatives to the traditional prospective population-based epidemiologic collections.

METHODS

To accelerate genomic discovery with an emphasis on diverse populations, we--as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study--accessed all non-European American samples (n = 15,863) available in BioVU, the Vanderbilt University biorepository linked to de-identified electronic medical records, for genomic studies as part of the larger Population Architecture using Genomics and Epidemiology (PAGE) I study. Given previous studies have cautioned against the secondary use of clinically collected data compared with epidemiologically collected data, we present here a characterization of EAGLE BioVU, including the billing and diagnostic (ICD-9) code distributions for adult and pediatric patients as well as comparisons made for select health metrics (body mass index, glucose, HbA1c, HDL-C, LDL-C, and triglycerides) with the population-based National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples (NHANES III, n = 7,159; NHANES 1999-2002, n = 7,839).

RESULTS

Overall, the distributions of billing and diagnostic codes suggest this clinical sample is a mixture of healthy and sick patients like that expected for a contemporary American population.

CONCLUSION

Little bias is observed among health metrics, suggesting this clinical collection is suitable for genomic studies along with traditional epidemiologic cohorts.

Obesity and genomics: role of technology in unraveling the complex genetic architecture of obesity

Obesity is a complex and multifactorial disease that occurs as a result of the interaction between "obesogenic" environmental factors and genetic components. Although the genetic component of obesity is clear from the heritability studies, the genetic basis remains largely elusive. Successes have been achieved in identifying the causal genes for monogenic obesity using animal models and linkage studies, but these approaches are not fruitful for polygenic obesity. The developments of genome-wide association approach have brought breakthrough discovery of genetic variants for polygenic obesity where tens of new susceptibility loci were identified. However, the common SNPs only accounted for a proportion of heritability. The arrival of NGS technologies and completion of 1000 Genomes Project have brought other new methods to dissect the genetic architecture of obesity, for example, the use of exome genotyping arrays and deep sequencing of candidate loci identified from GWAS to study rare variants. In this review, we summarize and discuss the developments of these genetic approaches in human obesity.

Genome-wide linkage scan identifies two novel genetic loci for coronary artery disease: in GeneQuest families

Coronary artery disease (CAD) is the leading cause of death worldwide. Recent genome-wide association studies (GWAS) identified >50 common variants associated with CAD or its complication myocardial infarction (MI), but collectively they account for <20% of heritability, generating a phenomena of “missing heritability”. Rare variants with large effects may account for a large portion of missing heritability. Genome-wide linkage studies of large families and follow-up fine mapping and deep sequencing are particularly effective in identifying rare variants with large effects. Here we show results from a genome-wide linkage scan for CAD in multiplex GeneQuest families with early onset CAD and MI. Whole genome genotyping was carried out with 408 markers that span the human genome by every 10 cM and linkage analyses were performed using the affected relative pair analysis implemented in GENEHUNTER. Affected only nonparametric linkage (NPL) analysis identified two novel CAD loci with highly significant evidence of linkage on chromosome 3p25.1 (peak NPL  = 5.49) and 3q29 (NPL  = 6.84). We also identified four loci with suggestive linkage on 9q22.33, 9q34.11, 17p12, and 21q22.3 (NPL  = 3.18–4.07). These results identify novel loci for CAD and provide a framework for fine mapping and deep sequencing to identify new susceptibility genes and novel variants associated with risk of CAD.

Current novel-gene-finding strategy for autosomal-dominant hypercholesterolaemia needs refinement

AIMS

Autosomal-dominant hypercholesterolaemia (ADH) is a heterogeneous common disorder, and uncovering the molecular determinants that underlie ADH is a major focus of cardiovascular research. However, despite rapid technical advances, efforts to identify novel ADH genes have yet not been very successful and are largely challenged by phenotypic and genetic heterogeneity of this disease. We aimed to investigate the impact of this phenotypic heterogeneity on successfully finding new genes that are involved in ADH.

METHODS AND RESULTS

For the ADH phenotype, subjects are considered as affected according to plasma cholesterol levels above the 95th percentile for age and gender. The disease penetrance is generally set at 0.9. These parameters were evaluated in 10000 carriers of true pathogenic APOB and LDLR mutations and 20000 relatives negative for the familial mutations. Application of the above parameters in almost a thousand families included in this study would have identified the causal variant in only 38% of all families. An average penetrance of 0.9 or higher, with a cut-point at the 95th percentile, was only observed for LDLR nonsense mutations. For APOB and LDLR missense mutations, a disease penetrance of 0.9 or higher is only expected, when total cholesterol and low-density lipoprotein cholesterol cut-points between the 75th and 90th percentile are used to determine an individual's disease status.

CONCLUSIONS

Although pathogenic LDLR and APOB mutations do follow Mendelian patterns of inheritance, the extensive variation in genotype and phenotype for well-known ADH-causing mutations emphasises that current criteria and strategies indeed are likely to hamper the identification of novel genes related to ADH. These findings provide a basis for the revision of our assessment on who is affected and who is not and emphasise the essence of pedigree information and mapping data before exome sequencing is applied in order to increase success rates of finding new genes related to ADH.

Host genetic studies in adult pulmonary tuberculosis

Early observations, candidate gene studies and, more recently, genome-wide association studies have shown that susceptibility to tuberculosis has a host genetic component. Because the value of candidate gene studies has been doubted due to major limitations such as lack of sufficient power and small study groups, lack of reproducibility in independent groups and, often, ambiguous or even contrasting results in attempts of replication, much hope and expectancy has been put on the progress the genome-wide association approach has created. However, much less than initially expected became clear by the results obtained in genome-wide studies, emphasizing the need of increasing sample sizes, e.g. through meta-analyses, and of increasing the density of genetic variants studied across the human genome. A further reason why a rather low number of associated genetic variants were identified to date in infectious diseases in general and tuberculosis in particular might be the fact that selection acts strongly in diseases that affect the reproductive success. As in most genome-wide association studies performed so far, significant signals, often most likely surrogate marker only, have been found in non-coding regions of genomes, the identification of truly causative genetic variation and of the functionality of associated factors needs urgent attention. In the following we briefly discuss genetic studies in tuberculosis and describe new technologies that are currently employed in the search for responsible genetic elements involved in tuberculosis susceptibility.

Efficient application of next-generation sequencing for the diagnosis of rare genetic syndromes

AIMS

The causes of intellectual disability, which affects 1%-3% of the general population, are highly heterogeneous and the genetic defect remains unknown in around 40% of patients. The application of next-generation sequencing is changing the nature of biomedical diagnosis. This technology has quickly become the method of choice for searching for pathogenic mutations in rare uncharacterised genetic diseases.

METHODS

Whole-exome sequencing was applied to a series of families affected with intellectual disability in order to identify variants underlying disease phenotypes.

RESULTS

We present data of three families in which we identified the disease-causing mutations and which benefited from receiving a clinical diagnosis: Cornelia de Lange, Cohen syndrome and Dent-2 disease. The genetic heterogeneity and the variability in clinical presentation of these disorders could explain why these patients are difficult to diagnose.

CONCLUSIONS

The accessibility to next-generation sequencing allows clinicians to save much time and cost in identifying the aetiology of rare diseases. The presented cases are excellent examples that demonstrate the efficacy of next-generation sequencing in rare disease diagnosis.

Genetics of keratoconus: where do we stand?

Keratoconus is a progressive thinning and anterior protrusion of the cornea that results in steepening and distortion of the cornea, altered refractive powers, and reduced vision. Keratoconus has a complex multifactorial etiology, with environmental, behavioral, and multiple genetic components contributing to the disease pathophysiology. Using genome-wide and candidate gene approaches several genomic loci and genes have been identified that highlight the complex molecular etiology of this disease. The review focuses on current knowledge of these genetic risk factors associated with keratoconus.

Jumping on the Train of Personalized Medicine: A Primer for Non-Geneticist Clinicians: Part 2. Fundamental Concepts in Genetic Epidemiology

With the decrease in sequencing costs, personalized genome sequencing will eventually become common in medical practice. We therefore write this series of three reviews to help non-geneticist clinicians to jump into the fast-moving field of personalized medicine. In the first article of this series, we reviewed the fundamental concepts in molecular genetics. In this second article, we cover the key concepts and methods in genetic epidemiology including the classification of genetic disorders, study designs and their implementation, genetic marker selection, genotyping and sequencing technologies, gene identification strategies, data analyses and data interpretation. This review will help the reader critically appraise a genetic association study. In the next article, we will discuss the clinical applications of genetic epidemiology in the personalized medicine area.

Mutations in STAP1 are associated with autosomal dominant hypercholesterolemia

RATIONALE

Autosomal-dominant hypercholesterolemia (ADH) is characterized by elevated low-density lipoprotein cholesterol levels and increased risk for coronary vascular disease. ADH is caused by mutations in the low-density lipoprotein receptor, apolipoprotein B, or proprotein convertase subtilisin/kexin 9. A number of patients, however, suffer from familial hypercholesterolemia 4 (FH4), defined as ADH in absence of mutations in these genes and thereafter use the abbreviation FH4.

OBJECTIVE

To identify a fourth locus associated with ADH.

METHODS AND RESULTS

Parametric linkage analysis combined with exome sequencing in a FH4 family resulted in the identification of the variant p.Glu97Asp in signal transducing adaptor family member 1 (STAP1), encoding signal transducing adaptor family member 1. Sanger sequencing of STAP1 in 400 additional unrelated FH4 probands identified a second p.Glu97Asp carrier and 3 additional missense variants, p.Leu69Ser, p.Ile71Thr, and p.Asp207Asn. STAP1 carriers (n=40) showed significantly higher plasma total cholesterol and low-density lipoprotein cholesterol levels compared with nonaffected relatives (n=91).

CONCLUSIONS

We mapped a novel ADH locus at 4p13 and identified 4 variants in STAP1 that associate with ADH.

Genomics meets proteomics: identifying the culprits in disease

Genome-wide association studies (GWAS) revealed genomic risk loci that potentially have an impact on disease and phenotypic traits. This extensive resource holds great promise in providing novel directions for personalized medicine, including disease risk prediction, prevention and targeted medication. One of the major challenges that researchers face on the path between the initial identification of an association and precision treatment of patients is the comprehension of the biological mechanisms that underlie these associations. Currently, the focus to solve these questions lies on the integrative analysis of system-wide data on global genome variation, gene expression, transcription factor binding, epigenetic profiles and chromatin conformation. The generation of this data mainly relies on next-generation sequencing. However, due to multiple recent developments, mass spectrometry-based proteomics now offers additional, by the GWAS field so far hardly recognized possibilities for the identification of functional genome variants and, in particular, for the identification and characterization of (differentially) bound protein complexes as well as physiological target genes. In this review, we introduce these proteomics advances and suggest how they might be integrated in post-GWAS workflows. We argue that the combination of highly complementary techniques is powerful and can provide an unbiased, detailed picture of GWAS loci and their mechanistic involvement in disease.

Genetic counseling in post-genomic era: Don’t pretend to know the meaning of a gene mutation if you don’t know

In this post-genomic era, more and more susceptibility loci of many possible genetic diseases are published. As our knowledge about these susceptibility loci is limited and partial, we should be very careful and responsible when patients seek genetic counseling about these possible genetic diseases. We should apply Confucius’s principle about knowledge and information to genetic conseling, and tell the truth to our patients about what we know and what we do not know. Like many other cancers, breast cancer is a very complicated, multifactorial disease; genetic factors, lifestyles and eating habits, environmental factors, and viral infections might be involved in breast cancer; hence, it is difficult to figure out the real etiology of breast cancer. It is not crystal clear that a person who carries mutations of the breast cancer 1, early onset and/or breast cancer 2, early onset genes would eventually get breast cancer in her/his lifetime. No person should undergo a preventive double mastectomy, unless we know the etiology of breast cancer someday.

The interaction effects of pri-let-7a-1 rs10739971 with PGC and ERCC6 gene polymorphisms in gastric cancer and atrophic gastritis

Background

The aim of this study was to investigate the interaction effects of pri-let-7a-1 rs10739971 with pepsinogen C (PGC) and excision repair cross complementing group 6 (ERCC6) gene polymorphisms and its association with the risks of gastric cancer and atrophic gastritis. We hoped to identify miRNA polymorphism or a combination of several polymorphisms that could serve as biomarkers for predicting the risk of gastric cancer and its precancerous diseases.

Methods

Sequenom MassARRAY platform method was used to detect polymorphisms of pri-let-7a-1 rs10739971 G→A, PGC rs4711690 C→G, PGC rs6458238 G→A, PGC rs9471643 G→C, and ERCC6 rs1917799 in 471 gastric cancer patients, 645 atrophic gastritis patients and 717 controls.

Results

An interaction effect of pri-let-7a-1 rs10739971 polymorphism with ERCC6 rs1917799 polymorphism was observed for the risk of gastric cancer (P_interaction = 0.026); and interaction effects of pri-let-7a-1 rs10739971 polymorphism with PGC rs6458238 polymorphism (P_interaction = 0.012) and PGC rs9471643 polymorphism (P_interaction = 0.039) were observed for the risk of atrophic gastritis.

Conclusion

The combination of pri-let-7a-1 rs10739971 polymorphism and ERCC6 and PGC polymorphisms could provide a greater prediction potential than a single polymorphism on its own. Large-scale studies and molecular mechanism research are needed to confirm our findings.

Using genetic prediction from known complex disease Loci to guide the design of next-generation sequencing experiments

A central focus of complex disease genetics after genome-wide association studies (GWAS) is to identify low frequency and rare risk variants, which may account for an important fraction of disease heritability unexplained by GWAS. A profusion of studies using next-generation sequencing are seeking such risk alleles. We describe how already-known complex trait loci (largely from GWAS) can be used to guide the design of these new studies by selecting cases, controls, or families who are most likely to harbor undiscovered risk alleles. We show that genetic risk prediction can select unrelated cases from large cohorts who are enriched for unknown risk factors, or multiply-affected families that are more likely to harbor high-penetrance risk alleles. We derive the frequency of an undiscovered risk allele in selected cases and controls, and show how this relates to the variance explained by the risk score, the disease prevalence and the population frequency of the risk allele. We also describe a new method for informing the design of sequencing studies using genetic risk prediction in large partially-genotyped families using an extension of the Inside-Outside algorithm for inference on trees. We explore several study design scenarios using both simulated and real data, and show that in many cases genetic risk prediction can provide significant increases in power to detect low-frequency and rare risk alleles. The same approach can also be used to aid discovery of non-genetic risk factors, suggesting possible future utility of genetic risk prediction in conventional epidemiology. Software implementing the methods in this paper is available in the R package Mangrove.

Genome-wide association studies in asthma: what they really told us about pathogenesis

PURPOSE OF REVIEW

Over the past years, several consortia have provided a data deluge from large-scale, genome-wide association studies (GWASs) for numerous asthma and allergy related traits. Dozens of reviews have already summarized the main results, although a coherent picture is still missing, referred to as 'missing' or 'unexplained' heritability.

RECENT FINDINGS

We identify the factors responsible for the unexplained heritability including imprecise phenotyping, biased single-nucleotide polymorphism selection (preferentially gene-based and high allele frequency with poor linkage disequilibrium tagging capacity), heterogeneity and insufficient significance ranking test statistics. In spite of these problems, three major outcomes can already be identified. First, rare variants give the highest risk estimates but are limited to small subgroups indicating a complex origin of asthma that may involve hundreds of variants that are either population, family or individual specific. Second, only a few common variants are shared amongst all asthmatics where the IL33/ST2 pathway turns out to be the most relevant factor. Third, transcription factor binding sites are enriched amongst the top association results pointing towards disturbed regulatory network function in asthma.

SUMMARY

The next wave of asthma genetic studies will use full-genome sequencing and overcome most GWAS-associated problems. It will be the last step of a century-long search for asthma genes, satisfying scientific curiosity and, hopefully, also providing data applicable in translational medicine.

Rare variants in complex traits: novel identification strategies and the role of de novo mutations

Following the limited success of linkage and association studies aimed at identifying the genetic causes of common neurodevelopmental syndromes like autism and schizophrenia, complex traits such as these have recently been considered under the 'common disease-rare variant' hypothesis. Prior to this hypothesis, the study of candidate genes has enabled the discovery of rare variants in complex disorders, and in turn some of these variants have highlighted the genetic contribution of de novo variants. De novo variants belong to a subcategory of spontaneous rare variants that are largely associated with sporadic diseases, which include some complex psychiatric disorders where the affected individuals do not transmit the genetic defects they carry because of their reduced reproductive fitness. Interestingly, recent studies have demonstrated the rate of germline de novo mutations to be higher in individuals with complex psychiatric disorders by comparison to what is seen in unaffected control individuals; moreover, de novo mutations carried by affected individuals have generally been more deleterious than those observed in control individuals. Advanced sequencing technologies have recently enabled the undertaking of massive parallel sequencing projects that can cover the entire coding sequences (exome) or genome of several individuals at once. Such advances have thus fostered the emergence of novel genetic hypotheses and ideas to investigate disease-causative genetic variations. The genetic underpinnings of a number of sporadic complex diseases is now becoming partly explained and more major breakthroughs for complex traits genomics should be expected in the near future.

The fibromyalgia family study: a genome-wide linkage scan study

OBJECTIVE

Familial aggregation of fibromyalgia has been increasingly recognized. The goal of this study was to conduct a genome-wide linkage scan to identify susceptibility loci for fibromyalgia.

METHODS

We genotyped members of 116 families from the Fibromyalgia Family Study and performed a model-free genome-wide linkage analysis of fibromyalgia with 341 microsatellite markers, using the Haseman-Elston regression approach.

RESULTS

The estimated sibling recurrence risk ratio (λs ) for fibromyalgia was 13.6 (95% confidence interval 10.0-18.5), based on a reported population prevalence of 2%. Genome-wide suggestive evidence of linkage was observed at markers D17S2196 (empirical P [Pe ]=0.00030) and D17S1294 (Pe=0.00035) on chromosome 17p11.2-q11.2.

CONCLUSION

The estimated sibling recurrence risk ratio (λs ) observed in this study suggests a strong genetic component of fibromyalgia. This is the first report of genome-wide suggestive linkage of fibromyalgia to the chromosome 17p11.2-q11.2 region. Further investigation of these multicase families from the Fibromyalgia Family Study is warranted to identify potential causal risk variants for fibromyalgia.