Genome-wide association studies: results from the first few years and potential implications for clinical medicine

Team players in the pathogenesis of metabolic dysfunctions-associated steatotic liver disease: The basis of development of pharmacotherapy

Nutrient metabolism is regulated by several factors. Social determinants of health with or without genetics are the primary regulator of metabolism, and an unhealthy lifestyle affects all modulators and mediators, leading to the adaptation and finally to the exhaustion of cellular functions. Hepatic steatosis is defined by presence of fat in more than 5% of hepatocytes. In hepatocytes, fat is stored as triglycerides in lipid droplet. Hepatic steatosis results from a combination of multiple intracellular processes. In a healthy individual nutrient metabolism is regulated at several steps. It ranges from the selection of nutrients in a grocery store to the last step of consumption of ATP as an energy or as a building block of a cell as structural component. Several hormones, peptides, and genes have been described that participate in nutrient metabolism. Several enzymes participate in each nutrient metabolism as described above from ingestion to generation of ATP. As of now several publications have revealed very intricate regulation of nutrient metabolism, where most of the regulatory factors are tied to each other bidirectionally, making it difficult to comprehend chronological sequence of events. Insulin hormone is the primary regulator of all nutrients' metabolism both in prandial and fasting states. Insulin exerts its effects directly and indirectly on enzymes involved in the three main cellular function processes; metabolic, inflammation and repair, and cell growth and regeneration. Final regulators that control the enzymatic functions through stimulation or suppression of a cell are nuclear receptors in especially farnesoid X receptor and peroxisome proliferator-activated receptor/RXR ligands, adiponectin, leptin, and adiponutrin. Insulin hormone has direct effect on these final modulators. Whereas blood glucose level, serum lipids, incretin hormones, bile acids in conjunction with microbiota are intermediary modulators which are controlled by lifestyle. The purpose of this review is to overview the key players in the pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD) that help us understand the disease natural course, risk stratification, role of lifestyle and pharmacotherapy in each individual patient with MASLD to achieve personalized care and target the practice of precision medicine. PubMed and Google Scholar databases were used to identify publication related to metabolism of carbohydrate and fat in states of health and disease states; MASLD, cardiovascular disease and cancer. More than 1000 publications including original research and review papers were reviewed.

Candidate genes related to acute cerebral circulatory disorders in Preeclampsia in the Kazakh Population

BACKGROUND

The purpose of this study is to conduct a comparative analysis of the population frequencies of alleles and genotypes of polymorphic variants of coagulation and fibrinolysis genes SERPINE1 rs1799889, ITGA2 rs1126643, THBD rs1042580, FII rs1799963, FV rs6025, FVII rs6046, angiogenesis and endothelial dysfunction PGF rs12411, FLT1 rs4769612, KDR rs2071559, ACE rs4340, GWAS associated with the development of acute cerebral circulatory disorders in preeclampsia, in an ethnically homogeneous population of Kazakhs with previously studied populations of the world.

METHODS

The genomic database was analysed based on the results of genotyping of 1800 conditionally healthy individuals of Kazakh nationality ∼2.5 million SNPs using OmniChip 2.5 M Illumina chips at the DECODE Iceland Genomic Center as part of the joint implementation of the project "Genetic Studies of Preeclampsia in Populations of Central Asia and Europe" (InterPregGen) within the 7th Framework Programme of the European Commission under Grant Agreement No. 282540.

RESULT

The study discovered a significantly higher population frequency of carrying the unfavorable rs1126643 allele of the ITGA2 gene polymorphism when compared with European populations. The population frequencies of carrying minor alleles of the SERPINE1 (rs179988) and KDR (rs2071559) genes in the Kazakh population were significantly lower when compared with the previously studied populations of Europe and Asia. An intermediate frequency of unfavorable minor alleles between European and Asian populations was found in Kazakhs for gene polymorphisms: FV rs6025, PGF rs12411, and ACE rs4340. The genomic analysis determined the choice of polymorphisms for their further replicative genotyping in patients with ACCD in PE in the Kazakh population.

CONCLUSION

The obtained results will serve as a basis for the development of effective methods of early diagnosis and treatment of PE in pregnant women, carriers of unfavorable genotypes.

Diabetes mellitus susceptibility with varied diseased phenotypes and its comparison with phenome interactome networks

An emerging area of interest in understanding disease phenotypes is systems genomics. Complex diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations. A wide number of methods have been employed and strategies such as polygenic risk score and allele frequencies have been useful, but understanding the candidate genes harboring those mutations is an unmet goal. In this perspective, using systems genomic approaches, we highlight the application of phenome-interactome networks in diabetes and provide deep insights. LINC01128, which we previously described as candidate for diabetes, is shown as an example to discuss the approach.

The role of genetic mutation in alcoholic liver disease

Background

Alcoholic liver disease (ALD) is the world’s most common type of liver disease caused due to overconsumption of alcohol. The liver supports the best level of tissue damage by hefty drinking since it is the binding site of ethanol digestion. This disease can progress to alcoholic steatohepatitis from alcoholic fatty liver, which implies steatosis has become the most punctual reaction to hefty drinking and is portrayed by the deposition of fat hepatocytes. In addition, steatosis can advance to steatohepatitis, a more extreme, provocative sort of liver damage described by hepatic inflammation. Constant and unnecessary liquor utilization delivers a wide range of hepatic sores, fibrosis and cirrhosis, and sometimes hepatocellular carcinoma. Most people consuming > 40 g of liquor each day create alcoholic fatty liver (AFL); notwithstanding, just a subset of people will grow further developed infection. Hereditary, epigenetic, and non-hereditary components may clarify the impressive interindividual variety in the ALD phenotype.

Main body

This systematic review is to classify new candidate genes associated with alcoholic liver disorders, such as RASGRF2, ALDH2, NFE2L2, ADH1B, PNPLA3, DRD2, MTHFR, TM6SF2, IL1B, and CYP2E1, MBOAT7 as well as to revise the functions of each gene in its polymorphic sequence. The information obtained from the previously published articles revealed the crucial relationship between the genes and ALD and discussed each selected gene’s mechanism.

Conclusion

The aim of this review is to highlight the candidate genes associated with the ALD, and the evidence of this study is to deliberate the part of genetic alterations and modifications that can serve as an excellent biological maker, risk predictors, and therapeutic targets for this disease.

Immunogenetic aspects of idiopathic recurrent miscarriage in the Kazakh population

There are numerous scientific studies of recurrent miscarriage (RM) with possible causes, such as fetal chromosomal abnormalities, infectious agents, adverse environmental factors, bad habits, anatomical defects, thrombophilic disorders, etc. However, RM causes in 50% of cases remain unknown. These RM cases do not have any explainable etiology, and they require in-depth etiopathogenesis study, thus they are considered idiopathic RM. The purpose of this research is to study polymorphisms relationship of the immune response genes CX3CR1 (rs3732379, Val249Ile), CTLA4 (rs3087243, CT60 G/A), and HLA DQA1, DQB1, DRB1 (major histocompatibility complex, class II) with the idiopathic form of recurrent miscarriage (iRM) development in Kazakh population. Independent replicative TagMan genotyping for 302 patients with iRM and 300 women with normal reproduction was performed. It has been shown that carriage of unfavorable genotypes (Val/Ile, Val/Val) by the Val249Ile polymorphism of the CX3CR1 gene increases the risk of developing iRM by 1.43 times. Search for associations of genes allelic variants of HLA class 2 complex with iRM revealed *501 allele in DQA1 locus, *0301 in DQB1 locus, *10, *12, *15, *16 alleles in DRB1 locus, which increases the risk of developing iRM in Kazakh population with OR from 1.34 to 4.5. As a result of the study, obtained highly significant associations of immune response genes with the development of iRM in the Kazakh population indicate the possible involvement of the immune system interaction of mother cells with syncytiotrophoblast, which is realized by vascularization defects, defective embryo implantation, and leads to early pregnancies’ termination.

The Immunogenetics of Vitiligo: An Approach Toward Revealing the Secret of Depigmentation

Vitiligo is a hypomelanotic skin disease and considered to be of autoimmune origin due to breaching of immunological self-tolerance, resulting in inappropriate immune responses against melanocytes. The development of vitiligo includes a strong heritable component. Different strategies ranging from linkage studies to genome-wide association studies are used to explore the genetic factors responsible for the disease. Several vitiligo loci containing the respective genes have been identified which contribute to vitiligo and genetic variants for some of the genes are still unknown. These genes include mainly the proteins that play a role in immune regulation and a few other genes important for apoptosis and regulation of melanocyte functions. Despite the available data on genetic variants and risk alleles which influence the biological processes, only few immunological pathways have been found responsible for all ranges of severity and clinical manifestations of vitiligo. However, studies have concluded that vitiligo is of autoimmune origin and manifests due to complex interactions in immune components and their inappropriate response toward melanocytes. The genes involved in the immune regulation and processing the melanocytes antigen and its presentation can serve as effective immune-therapeutics that can target specific immunological pathways involved in vitiligo. This chapter highlights those immune-regulatory genes involved in vitiligo susceptibility and loci identified to date and their implications in vitiligo pathogenesis.

Arterial Hypertension: Individual Therapeutic Approaches-From DNA Sequencing to Gender Differentiation and New Therapeutic Targets

The aim of this paper is to provide an accurate overview regarding the current recommended approach for antihypertensive treatment. The importance of DNA sequencing in understanding the complex implication of genetics in hypertension could represent an important step in understanding antihypertensive treatment as well as in developing new medical strategies. Despite a pool of data from studies regarding cardiovascular risk factors emphasizing a worse prognosis for female patients rather than male patients, there are also results indicating that women are more likely to be predisposed to the use of antihypertensive medication and less likely to develop uncontrolled hypertension. Moreover, lower systolic blood pressure values are associated with increased cardiovascular risk in women compared to men. The prevalence, awareness and, most importantly, treatment of hypertension is variable in male and female patients, since the mechanisms responsible for this pathology may be different and closely related to gender factors such as the renin–angiotensin system, sympathetic nervous activity, endothelin-1, sex hormones, aldosterone, and the immune system. Thus, gender-related antihypertensive treatment individualization may be a valuable tool in improving female patients’ prognosis.

Genetic Structural Differentiation Analyses of Intercontinental Populations and Ancestry Inference of the Chinese Hui Group Based on a Novel Developed Autosomal AIM-InDel Genotyping System

In the present study, we investigated the genetic polymorphisms of 39 ancestry informative marker-insertion/deletion (AIM-InDel) loci in the Chinese Hui group using a previously self-developed panel, further clarified the genetic relationships between the Hui group and other reference populations, and assessed the ancestry inference efficiency of the AIM-InDel panel based on the worldwide population data from 1000 Genomes Phase 3. The results of the locus-specific informativeness (I_n) and pairwise fixation index (F_st) values, multidimensional scaling analysis, and success ratio of estimation with cross-validation showed that the novel panel could well reveal the genetic structural differentiations of the East Asian, European, African, and South Asian populations. Besides, the biogeographical ancestry origin inference both at the individual and population levels was conducted on the Chinese Hui group by principal component analysis and STRUCTURE analysis, and the results revealed that the Hui group had the East Asian origin, and the East Asian component ratio of Hui group was approximately 88.87%. Furthermore, the population genetic analyses among the Hui group and reference populations were performed based on the insertion allele frequency heat map, population pairwise F_st values and phylogenetic tree, and the results indicated that the Hui group was genetically closer to East Asian populations, especially two Chinese Han populations (CHS and CHB populations).

Nonalcoholic fatty liver disease and cardiovascular disease phenotypes

Nonalcoholic fatty liver disease is increasingly recognized as a major global health problem. Intertwined with diabetes, metabolic syndrome, and obesity, nonalcoholic fatty liver disease embraces a spectrum of liver conditions spanning from steatosis to inflammation, fibrosis, and liver failure. Compared with the general population, the prevalence of cardiovascular disease is higher among nonalcoholic fatty liver disease patients, in whom comprehensive cardiovascular risk assessment is highly desirable. Preclinical effects of nonalcoholic fatty liver disease on the heart include both metabolic and structural changes eventually preceding overt myocardial dysfunction. Particularly, nonalcoholic fatty liver disease is associated with enhanced atherosclerosis, heart muscle disease, valvular heart disease, and arrhythmias, with endothelial dysfunction, inflammation, metabolic dysregulation, and oxidative stress playing in the background. In this topical review, we aimed to summarize current evidence on the epidemiology of nonalcoholic fatty liver disease, discuss the pathophysiological links between nonalcoholic fatty liver disease and cardiovascular disease, illustrate nonalcoholic fatty liver disease-related cardiovascular phenotypes, and finally provide a glimpse on the relationship between nonalcoholic fatty liver disease and cardiac steatosis, mitochondrial (dys)function, and cardiovascular autonomic dysfunction.

Development and optimization of a hybridization technique to type the classical class I and class II B genes of the chicken MHC

The classical class I and class II molecules of the major histocompatibility complex (MHC) play crucial roles in immune responses to infectious pathogens and vaccines as well as being important for autoimmunity, allergy, cancer and reproduction. These classical MHC genes are the most polymorphic known, with roughly 10,000 alleles in humans. In chickens, the MHC (also known as the BF-BL region) determines decisive resistance and susceptibility to infectious pathogens, but relatively few MHC alleles and haplotypes have been described in any detail. We describe a typing protocol for classical chicken class I (BF) and class II B (BLB) genes based on a hybridization method called reference strand-mediated conformational analysis (RSCA). We optimize the various steps, validate the analysis using well-characterized chicken MHC haplotypes, apply the system to type some experimental lines and discover a new chicken class I allele. This work establishes a basis for typing the MHC genes of chickens worldwide and provides an opportunity to correlate with microsatellite and with single nucleotide polymorphism (SNP) typing for approaches involving imputation.

The framework for population epigenetic study

At present, understanding of DNA methylation at the population level is still limited. Here, we first extended the classical framework of population genetics, such as single nucleotide polymorphism allele frequency, linkage disequilibrium (LD), LD block and haplotype, to epigenetics. Then, as an example, we compared the DNA methylation disequilibrium (MD) maps between HapMap CEU (Caucasian residents of European ancestry from Utah) population and YRI (Yoruba people from Ibadan) population (lymphoblastoid cell lines). We analyzed the differences and similarities between CEU and YRI from the following aspects: SMP (single methylation polymorphism) allele frequency, SMP allele association, MD, MD block and methylation haplotype (meplotype) frequency. The results showed that CEU and YRI had similar distribution of SMP allele frequency, and shared many MD block region. We believe that the framework of population genetics can be used in the population epigenetics. The population epigenetic framework also has potential prospects in the study of complex diseases, such as epigenome-wide association study.

Association between the CYBA and NOX4 genes of NADPH oxidase and its relationship with metabolic syndrome in non-alcoholic fatty liver disease in Brazilian population

BACKGROUND

Oxidative stress has been implicated in the progression of severe forms of non-alcoholic fatty liver disease (NAFLD). NADPH oxidase produces reactive oxygen species. In the present study, we investigated for the first time two single nucleotide polymorphisms (SNPs) in the regulatory region of genes encoding NADPH oxidase 4 (NOX4) and p22phox (CYBA) in NAFLD.

METHODS

A total of 207 biopsy-proven NAFLD patients [simple steatosis (n = 27); nonalcoholic steatohepatitis (NASH) (n = 180)] were evaluated. Genomic DNA was extracted from peripheral blood cells, and polymorphisms in CYBA (unregistered) and NOX4 (rs3017887) were determined by direct sequencing of PCR.

RESULTS

Associations of CYBA-675 T/A with high-density lipoprotein (HDL) (TT vs TA vs AA; P < 0.01) and triglycerides (TGL) (TT vs XA; P < 0.01) were observed only in NASH patients. For polymorphisms in the NOX4 gene, NOX4 (rs3017887) CA + AA genotypes was significant associated with alanine aminotransferase (ALT) (CA + AA vs CC; P = 0.02). However, there was no association of SNPs in the CYBA and NOX4 genes encoding the NADPH oxidase system proteins and the presence of NASH. Regarding the clinical results, it was observed that the most advanced degrees of fibrosis occurred in patients diagnosed with type 2 diabetes mellitus (66.9% vs 37.5%, P < 0.01) and those who were more obese (32.2 vs 29.0 kg/m², P < 0.01). In addition, serum glucose and insulin levels increased significantly in the presence of NASH.

CONCLUSIONS

There were associations between the presence of the allele A in the NOX4 SNP and a higher concentration of ALT in the NAFLD population; between the presence of the AA genotype in the polymorphism of the CYBA-675 T/A CYBA gene and a higher level of TGL and lower HDL in NASH patients. The presence of metabolic syndrome was associated with advanced degrees of fibrosis in NAFLD patients.

Identification of rare noncoding sequence variants in gamma-aminobutyric acid A receptor, alpha 4 subunit in autism spectrum disorder

Alterations of the gamma-aminobutyric acid (GABA) signaling system has been strongly linked to the pathophysiology of autism spectrum disorder (ASD). Genetic associations of common variants in GABA receptor subunits, in particular GABRA4 on chromosome 4p12, with ASD have been replicated by several studies. Moreover, molecular investigations have identified altered transcriptional and translational levels of this gene and protein in brains of ASD individuals. Since the genotyped common variants are likely not the functional variants contributing to the molecular consequences or underlying ASD phenotype, this study aims to examine rare sequence variants in GABRA4, including those outside the protein coding regions of the gene. We comprehensively re-sequenced the entire protein coding and noncoding portions of the gene and putative regulatory sequences in 82 ASD individuals and 55 developmentally typical pediatric controls, all homozygous for the most significant previously associated ASD risk allele (G/G at rs1912960). We identified only a single common, coding variant, and no association of any single marker or set of variants with ASD. Functional annotation of noncoding variants identified several rare variants in putative regulatory sites. Finally, a rare variant unique to ASD cases, in an evolutionary conserved site of the 3'UTR, shows a trend toward decreasing gene expression. Hence, GABRA4 rare variants in noncoding DNA may be variants of modest physiological effects in ASD etiology.

Genome-Wide Association Studies for Idiosyncratic Drug-Induced Hepatotoxicity: Looking Back-Looking Forward to Next-Generation Innovation

Idiosyncratic drug-induced hepatotoxicity is a formidable challenge for rational drug discovery and development, as well as the science of personalized medicine. There is evidence that hereditary factors, in part, contribute to drug toxicity. This expert analysis and review offer the insights gained, and the challenges ahead, for genome-wide association studies (GWASs) of idiosyncratic drug-induced hepatotoxicity. Published articles on genome-wide and subsequent replication studies were systematically searched in the PubMed electronic database. We found that the genetic risk variants that were identified genome-wide, and replication confirmed, are mainly related to polymorphisms in the human leukocyte antigen (HLA) region that include HLA-DQB1*06:02 for amoxicillin-clavulanate, HLA-B*57:01 for flucloxacillin, HLA-DRB1*15:01 for lumiracoxib, and HLA-DRB1*07:01 for lapatinib and ximelagatran-induced hepatotoxicity. Additionally, polymorphisms in ST6 β-galactosamide α-2, 6-sialyltranferase-1 (ST6GAL1), which plays a role in systemic inflammatory response, and variants in intron of family with sequence similarity-65 member-B (FAM65B) that play roles in liver inflammation displayed association with flucloxacillin and antituberculosis drug-induced hepatotoxicity, respectively. Taken together, these GWAS findings offer molecular leads on the central role that the immune system plays in idiosyncratic drug-induced hepatotoxicity. We conclude the expert review with a brief discussion of the salient challenges ahead. These include, for example, the need for discursive discovery paradigms that incorporate alternating GWASs and candidate gene studies, as well as the study of the environtome, the entire complement of environmental factors, including science and innovation policies that enact on global society and the human host, and by extension, on susceptibility for idiosyncratic drug-induced hepatotoxicity.

EWAS: epigenome-wide association studies software 1.0 - identifying the association between combinations of methylation levels and diseases

Similar to the SNP (single nucleotide polymorphism) data, there is non-random association of the DNA methylation level (we call it methylation disequilibrium, MD) between neighboring methylation loci. For the case-control study of complex diseases, it is important to identify the association between methylation levels combination types (we call it methylecomtype) and diseases/phenotypes. We extended the classical framework of SNP haplotype-based association study in population genetics to DNA methylation level data, and developed a software EWAS to identify the disease-related methylecomtypes. EWAS can provide the following basic functions: (1) calculating the DNA methylation disequilibrium coefficient between two CpG loci; (2) identifying the MD blocks across the whole genome; (3) carrying out case-control association study of methylecomtypes and identifying the disease-related methylecomtypes. For a DNA methylation level data set including 689 samples (354 cases and 335 controls) and 473864 CpG loci, it takes only about 25 min to complete the full scan. EWAS v1.0 can rapidly identify the association between combinations of methylation levels (methylecomtypes) and diseases. EWAS v1.0 is freely available at: http://www.ewas.org.cn or http://www.bioapp.org/ewas.

Genetic Factors That Affect Risk of Alcoholic and Nonalcoholic Fatty Liver Disease

Genome-wide association studies and candidate gene studies have informed our understanding of factors contributing to the well-recognized interindividual variation in the progression and outcomes of alcoholic liver disease and nonalcoholic fatty liver disease. We discuss the mounting evidence for shared modifiers and common pathophysiological processes that contribute to development of both diseases. We discuss the functions of proteins encoded by risk variants of genes including patatin-like phospholipase domain-containing 3 and transmembrane 6 superfamily member 2, as well as epigenetic factors that contribute to the pathogenesis of alcoholic liver disease and nonalcoholic fatty liver disease. We also discuss important areas of future genetic research and their potential to affect clinical management of patients.

Advances in Genetic Testing for Hereditary Cancer Syndromes

The ability to identify genetic mutations causing an increased risk of cancer represents the first widespread example of personalised medicine, in which genetic information is used to inform patients of their cancer risks and direct an appropriate strategy to minimise those risks. Increasingly, an understanding of the genetic basis of many cancers also facilitates selection of the most effective therapeutic options. The technology underlying genetic testing has been revolutionised in the years since the completion of the Human Genome Project in 2001. This has advanced knowledge of the genetic factors underlying familial cancer risk, and has also improved genetic testing capacity allowing a larger number of patients to be tested for a constitutional cancer predisposition. To use these tests safely and effectively, they must be assessed for their ability to provide accurate and useful results, and be requested and interpreted by health professionals with an understanding of their strengths and limitations. Genetic testing is increasing in its scope and ambition with each year that passes, requiring a greater proportion of the healthcare workforce to acquire a working knowledge of genetics and genetic testing to manage their patients safely and sensitively.

TM6SF2 E167K Variant, a Novel Genetic Susceptibility Variant, Contributing to Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of liver dysfunction worldwide, and its prevalence is highly associated with genetic susceptibility. The transmembrane 6 superfamily member 2 (TM6SF2) E167K variant represents a general genetic determinant of hepatic triglyceride content and lobular inflammation, and its presence appears to be directly involved in the pathogenesis and development of NAFLD. Although this variant appears to be a novel powerful modifier in the development of NAFLD, whether it is associated with an increased risk of NAFLD-related liver fibrosis and hepatocellular carcinoma (HCC) remains to be determined. The aim of this review is to describe the functions of the TM6SF2 E167K variant and its association with NAFLD, with particular emphasis on the underlying mechanisms of its role in the development and progression of NAFLD. Additionally, the links between the TM6SF2 E167K variant and NAFLD-related liver fibrosis and HCC will be discussed.

Dexamethasone treatment alters insulin, leptin, and adiponectin levels in male mice as observed in DIO but does not lead to alterations of metabolic phenotypes in the offspring

Epigenetic inheritance (EI) of metabolic phenotypes via the paternal lineage has been shown in rodent models of diet-induced obesity (DIO). However, the factors involved in soma-to-germline information transfer remain elusive. Here, we address the role of alterations in insulin, leptin, and adiponectin levels for EI of metabolic phenotypes by treating C57BL/6NTac male mice (F0) with the synthetic glucocorticoid dexamethasone and generating offspring (F1) either by in vitro fertilization or by natural fecundation. Dexamethasone treatment slightly alters F0 body composition by increasing fat mass and decreasing lean mass, and significantly improves glucose tolerance. Moreover, it increases insulin and leptin levels and reduces adiponectin levels in F0 fathers as observed in mouse models of DIO. However, these paternal changes of metabolic hormones do not alter metabolic parameters, such as body weight, body composition and glucose homeostasis in male and female F1 mice even when these are challenged with a high-fat diet. Accordingly, sperm transcriptomes are not altered by dexamethasone treatment. Our results suggest that neither increased glucocorticoid, insulin, and leptin levels, nor decreased adiponectin levels in fathers are sufficient to confer soma-to-germline information transfer in EI of obesity via the paternal lineage.

Age-related macular degeneration: genome-wide association studies to translation

In recent years, genome-wide association studies (GWAS), which are able to analyze the contribution to disease of genetic variations that are common within a population, have attracted considerable investment. Despite identifying genetic variants for many conditions, they have been criticized for yielding data with minimal clinical utility. However, in this regard, age-related macular degeneration (AMD), the most common form of blindness in the Western world, is a striking exception. Through GWAS, common genetic variants at a number of loci have been discovered. Two loci in particular, including genes of the complement cascade on chromosome 1 and the ARMS2/HTRA1 genes on chromosome 10, have been shown to convey significantly increased susceptibility to developing AMD. Today, although it is possible to screen individuals for a genetic predisposition to the disease, effective interventional strategies for those at risk of developing AMD are scarce. Ongoing research in this area is nonetheless promising. After providing brief overviews of AMD and common disease genetics, we outline the main recent advances in the understanding of AMD, particularly those made through GWAS. Finally, the true merit of these findings and their current and potential translational value is examined.Genet Med 18 4, 283-289.

GWA meta-analysis of personality in Korean cohorts

Personality is a determinant of behavior and lifestyle that is associated with health and human diseases. Despite the heritability of personality traits is well established, the understanding of the genetic contribution to personality trait variation is extremely limited. To identify genetic variants associated with each of the five dimensions of personality, we performed a genome-wide association (GWA) meta-analysis of three cohorts, followed by comparison of a family cohort. Personality traits were measured with the Revised NEO Personality Inventory for the five-factor model (FFM) of personality. We investigated the top five single-nucleotide polymorphisms (SNPs) for each trait, and revealed the most highly association with neuroticism and TACC2 (rs1010657, P=8.79 × 10(-7)), extraversion and PTPN12 (rs12537271, P=1.47 × 10(-7)), openness and IMPAD1 (rs16921695, P=5 × 10(-8)), agreeableness and RPS29 (rs8015351, P=1.27 × 10(-6)) and conscientiousness and LMO4 (rs912765, P=2.91 × 10(-6)). It had no SNP reached the GWA study threshold (P<5 × 10(-8)). When expanded the SNPs up to top 100, the correlation of PTPRD (rs1029089) and agreeableness was confirmed in Healthy Twin cohort with other 13 SNPs. This GWA meta-analysis on FFM personality traits is meaningful as it was the first on a non-Caucasian population targeted to FFM of personality traits.

Genetics and heart failure: a concise guide for the clinician

The pathogenesis of heart failure involves a complex interaction between genetic and environmental factors. Genetic factors may influence the susceptibility to the underlying etiology of heart failure, the rapidity of disease progression, or the response to pharmacologic therapy. The genetic contribution to heart failure is relatively minor in most multifactorial cases, but more direct and profound in the case of familial dilated cardiomyopathy. Early studies of genetic risk for heart failure focused on polymorphisms in genes integral to the adrenergic and renin-angiotensin-aldosterone system. Some of these variants were found to increase the risk of developing heart failure, and others appeared to affect the therapeutic response to neurohormonal antagonists. Regardless, each variant individually confers a relatively modest increase in risk and likely requires complex interaction with other variants and the environment for heart failure to develop. Dilated cardiomyopathy frequently leads to heart failure, and a genetic etiology increasingly has been recognized in cases previously considered to be "idiopathic". Up to 50% of dilated cardiomyopathy cases without other cause likely are due to a heritable genetic mutation. Such mutations typically are found in genes encoding sarcomeric proteins and are inherited in an autosomal dominant fashion. In recent years, rapid advances in sequencing technology have improved our ability to diagnose familial dilated cardiomyopathy and those diagnostic tests are available widely. Optimal care for the expanding population of patients with heritable heart failure involves counselors and physicians with specialized training in genetics, but numerous online genetics resources are available to practicing clinicians.

Genetics and vaccines in the era of personalized medicine

Vaccines represent the most successful and sustainable tactic to prevent and counteract infection. A vaccine generally improves immunity to a particular disease upon administration by inducing specific protective and efficient immune responses in all of the receiving population. The main known factors influencing the observed heterogeneity for immune re-sponses induced by vaccines are gender, age, co-morbidity, immune system, and genetic background. This review is mainly focused on the genetic status effect to vaccine immune responses and how this could contribute to the development of novel vaccine candidates that could be better directed and predicted relative to the genetic history of an individual and/or population. The text offers a brief history of vaccinology as a field, a description of the genetic status of the most relevant and studied genes and their functionality and correlation with exposure to specific vaccines; followed by an inside look into autoimmunity as a concern when designing vaccines as well as perspectives and conclusions looking towards an era of personalized and predictive vaccinology instead of a one size fits all approach.

The IGF1 P2 promoter is an epigenetic QTL for circulating IGF1 and human growth

Background

Even if genetics play an important role, individual variation in stature remains unexplained at the molecular level. Indeed, genome-wide association study (GWAS) have revealed hundreds of variants that contribute to the variability of height but could explain only a limited part of it, and no single variant accounts for more than 0.3% of height variance. At the interface of genetics and environment, epigenetics contributes to phenotypic diversity. Quantifying the impact of epigenetic variation on quantitative traits, an emerging challenge in humans, has not been attempted for height. Since insulin-like growth factor 1 (IGF1) controls postnatal growth, we tested whether the CG methylation of the two promoters (P1 and P2) of the IGF1 gene is a potential epigenetic contributor to the individual variation in circulating IGF1 and stature in growing children.

Results

Child height was closely correlated with serum IGF1. The methylation of a cluster of six CGs located within the proximal part of the IGF1 P2 promoter showed a strong negative association with serum IGF1 and growth. The highest association was for CG-137 methylation, which contributed 13% to the variance of height and 10% to serum IGF1. CG methylation (studied in children undergoing surgery) was approximately 50% lower in liver and growth plates, indicating that the IGF1 promoters are tissue-differentially methylated regions (t-DMR). CG methylation was inversely correlated with the transcriptional activity of the P2 promoter in mononuclear blood cells and in transfection experiments, suggesting that the observed association of methylation with the studied traits reflects true biological causality.

Conclusions

Our observations introduce epigenetics among the individual determinants of child growth and serum IGF1. The P2 promoter of the IGF1 gene is the first epigenetic quantitative trait locus (QTL^epi) reported in humans. The CG methylation of the P2 promoter takes place among the multifactorial factors explaining the variation in human stature.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-015-0062-8) contains supplementary material, which is available to authorized users.

Intelligence: shared genetic basis between Mendelian disorders and a polygenic trait

Multiple inquiries into the genetic etiology of human traits indicated an overlap between genes underlying monogenic disorders (eg, skeletal growth defects) and those affecting continuous variability of related quantitative traits (eg, height). Extending the idea of a shared genetic basis between a Mendelian disorder and a classic polygenic trait, we performed an association study to examine the effect of 43 genes implicated in autosomal recessive cognitive disorders on intelligence in an unselected Dutch population (N=1316). Using both single-nucleotide polymorphism (SNP)- and gene-based association testing, we detected an association between intelligence and the genes of interest, with genes ELP2, TMEM135, PRMT10, and RGS7 showing the strongest associations. This is a demonstration of the relevance of genes implicated in monogenic disorders of intelligence to normal-range intelligence, and a corroboration of the utility of employing knowledge on monogenic disorders in identifying the genetic variability underlying complex traits.

TM6SF2 rs58542926 influences hepatic fibrosis progression in patients with non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is an increasingly common condition, strongly associated with the metabolic syndrome, that can lead to progressive hepatic fibrosis, cirrhosis and hepatic failure. Subtle inter-patient genetic variation and environmental factors combine to determine variation in disease progression. A common non-synonymous polymorphism in TM6SF2 (rs58542926 c.449 C>T, p.Glu167Lys) was recently associated with increased hepatic triglyceride content, but whether this variant promotes clinically relevant hepatic fibrosis is unknown. Here we confirm that TM6SF2 minor allele carriage is associated with NAFLD and is causally related to a previously reported chromosome 19 GWAS signal that was ascribed to the gene NCAN. Furthermore, using two histologically characterized cohorts encompassing steatosis, steatohepatitis, fibrosis and cirrhosis (combined n=1,074), we demonstrate a new association, independent of potential confounding factors (age, BMI, type 2 diabetes mellitus and PNPLA3 rs738409 genotype), with advanced hepatic fibrosis/cirrhosis. These findings establish new and important clinical relevance to TM6SF2 in NAFLD.

Non-alcoholic fatty liver disease (NAFLD) is characterized by increased hepatic triglyceride content (HTGC) in the absence of high alcohol consumption. Here the authors show that a genetic variant in TM6SF2, which is known to be associated with HTGC, is a clinically relevant modifier of hepatic fibrogenesis and increases the risk of progressive NAFLD.

Quality control and conduct of genome-wide association meta-analyses

Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC at the study file level, the meta-level across studies and the meta-analysis output level. Real-world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for the use of a powerful and flexible software package called EasyQC. Precise timings will be greatly influenced by consortium size. For consortia of comparable size to the GIANT Consortium, this protocol takes a minimum of about 10 months to complete.

Predicting gene ontology annotations of orphan GWAS genes using protein-protein interactions

Background

The number of genome-wide association studies (GWAS) has increased rapidly in the past couple of years, resulting in the identification of genes associated with different diseases. The next step in translating these findings into biomedically useful information is to find out the mechanism of the action of these genes. However, GWAS studies often implicate genes whose functions are currently unknown; for example, MYEOV, ANKLE1, TMEM45B and ORAOV1 are found to be associated with breast cancer, but their molecular function is unknown.

Results

We carried out Bayesian inference of Gene Ontology (GO) term annotations of genes by employing the directed acyclic graph structure of GO and the network of protein-protein interactions (PPIs). The approach is designed based on the fact that two proteins that interact biophysically would be in physical proximity of each other, would possess complementary molecular function, and play role in related biological processes. Predicted GO terms were ranked according to their relative association scores and the approach was evaluated quantitatively by plotting the precision versus recall values and F-scores (the harmonic mean of precision and recall) versus varying thresholds. Precisions of ~58% and ~ 40% for localization and functions respectively of proteins were determined at a threshold of ~30 (top 30 GO terms in the ranked list). Comparison with function prediction based on semantic similarity among nodes in an ontology and incorporation of those similarities in a k-nearest neighbor classifier confirmed that our results compared favorably.

Conclusions

This approach was applied to predict the cellular component and molecular function GO terms of all human proteins that have interacting partners possessing at least one known GO annotation. The list of predictions is available at http://severus.dbmi.pitt.edu/engo/GOPRED.html. We present the algorithm, evaluations and the results of the computational predictions, especially for genes identified in GWAS studies to be associated with diseases, which are of translational interest.

Cell therapies and regenerative medicine

Molecular and cell biology has resulted in major advances in our understanding of disease pathogenesis as well as in novel strategies for the diagnosis, therapy and prevention of human diseases. Based on modern molecular, genetic and biochemical methodologies, it is on the one hand possible to identify disease-related point mutations and single nucleotide polymorphisms, for example. On the other hand, using high throughput array and other technologies, it is for example possible to simultaneously analyze thousands of genes or gene products (RNA and proteins), resulting in an individual gene or gene expression profile ('signature'). Such data increasingly allow defining the individual disposition for a given disease and predicting disease prognosis as well as the efficacy of therapeutic strategies in the individual patient ('personalized medicine'). At the same time, the basic discoveries in cell biology, including embryonic and adult stem cells, induced pluripotent stem cells, genetically modified cells and others, have moved regenerative medicine into the center of biomedical research worldwide with a major translational impact on tissue engineering as well as transplantation medicine. All these aspects have greatly contributed to the recent advances in regenerative medicine and the development of novel concepts for the treatment of many human diseases, including liver diseases.

An excess of risk-increasing low-frequency variants can be a signal of polygenic inheritance in complex diseases

In most complex diseases, much of the heritability remains unaccounted for by common variants. It has been postulated that lower-frequency variants contribute to the remaining heritability. Here, we describe a method to test for polygenic inheritance from lower-frequency variants by using GWAS summary association statistics. We explored scenarios with many causal low-frequency variants and showed that there is more power to detect risk variants than to detect protective variants, resulting in an increase in the ratio of detected risk to protective variants (R/P ratio). Such an excess can also occur if risk variants are present and kept at lower frequencies because of negative selection. The R/P ratio can be falsely elevated because of reasons unrelated to polygenic inheritance, such as uneven sample sizes or asymmetric population stratification, so precautions to correct for these confounders are essential. We tested our method on published GWAS results and observed a strong signal in some diseases (schizophrenia and type 2 diabetes) but not others. We also explored the shared genetic component in overlapping phenotypes related to inflammatory bowel disease (Crohn disease [CD] and ulcerative colitis [UC]) and diabetic nephropathy (macroalbuminuria and end-stage renal disease [ESRD]). Although the signal was still present when both CD and UC were jointly analyzed, the signal was lost when macroalbuminuria and ESRD were jointly analyzed, suggesting that these phenotypes should best be studied separately. Thus, our method may also help guide the design of future genetic studies of various traits and diseases.

Advances in individualized and regenerative medicine

Molecular and cell biology have resulted in major advances in our understanding of disease pathogenesis as well as in novel strategies for the diagnosis, therapy and prevention of human diseases. Based on modern molecular, genetic and biochemical methodologies it is on the one hand possible to identify for example disease-related point mutations and single nucleotide polymorphisms. On the other hand, using high throughput array and other technologies, it is for example possible to simultaneously analyze thousands of genes or gene products (RNA and proteins), resulting in an individual gene or gene expression profile ('signature'). Such data increasingly allow to define the individual disposition for a given disease and to predict disease prognosis as well as the efficacy of therapeutic strategies in the individual patient ('individualized medicine'). At the same time, the basic discoveries in cell biology, including embryonic and adult stem cells, induced pluripotent stem cells, genetically modified cells and others, have moved regenerative medicine into the center of biomedical research worldwide with a major translational impact on tissue engineering as well as transplantation medicine. All these aspects have greatly contributed to the recent advances in regenerative medicine and the development novel concepts for the treatment of many human diseases, including liver diseases.

Personalized genomic results: analysis of informational needs

Use of genomic information in healthcare is increasing; however data on the needs of consumers of genomic information is limited. The Coriell Personalized Medicine Collaborative (CPMC) is a longitudinal study investigating the utility of personalized medicine. Participants receive results reflecting risk of common complex conditions and drug-gene pairs deemed actionable by an external review board. To explore the needs of individuals receiving genomic information we reviewed all genetic counseling sessions with CPMC participants. A retrospective qualitative review of notes from 157 genetic counseling inquiries was conducted. Notes were coded for salient themes. Five primary themes; "understanding risk", "basic genetics", "complex disease genetics", "what do I do now?" and "other" were identified. Further review revealed that participants had difficulty with basic genetic concepts, confused relative and absolute risks, and attributed too high a risk burden to individual single nucleotide polymorphisms (SNPs). Despite these hurdles, counseled participants recognized that behavior changes could potentially mitigate risk and there were few comments alluding to an overly deterministic or fatalistic interpretation of results. Participants appeared to recognize the multifactorial nature of the diseases for which results were provided; however education to understand the complexities of genomic risk information was often needed.

PNPLA3 I148M polymorphism and progressive liver disease

The 148 Isoleucine to Methionine protein variant (I148M) of patatin-like phospholipase domain-containing 3 (PNPLA3), a protein is expressed in the liver and is involved in lipid metabolism, has recently been identified as a major determinant of liver fat content. Several studies confirmed that the I148M variant predisposes towards the full spectrum of liver damage associated with fatty liver: from simple steatosis to steatohepatitis and progressive fibrosis. Furthermore, the I148M variant represents a major determinant of progression of alcohol related steatohepatitis to cirrhosis, and to influence fibrogenesis and related clinical outcomes in chronic hepatitis C virus hepatitis, and possibly chronic hepatitis B virus hepatitis, hereditary hemochromatosis and primary sclerosing cholangitis. All in all, studies suggest that the I148M polymorphism may represent a general modifier of fibrogenesis in liver diseases. Remarkably, the effect of the I148M variant on fibrosis was independent of that on hepatic steatosis and inflammation, suggesting that it may affect both the quantity and quality of hepatic lipids and the biology of non-parenchymal liver cells besides hepatocytes, directly promoting fibrogenesis. Therefore, PNPLA3 is a key player in liver disease progression. Assessment of the I148M polymorphism will possibly inform clinical practice in the future, whereas the determination of the effect of the 148M variant will reveal mechanisms involved in hepatic fibrogenesis.

The genetics of NAFLD

NAFLD is a disease spectrum ranging from simple steatosis, through steatohepatitis to fibrosis and, ultimately, cirrhosis. This condition is characterized by considerable interpatient variability in terms of severity and rate of progression: although a substantial proportion of the population is at risk of progressive disease, only a minority experience associated morbidity. As such, NAFLD is best considered a complex disease trait resulting from environmental exposures acting on a susceptible polygenic background and comprising multiple independent modifiers. Much ongoing research is focused on identifying the genetic factors that contribute to NAFLD pathogenesis. This Review describes the current status of the field, discussing specific genetic and epigenetic modifiers, including the mechanisms through which genes identified by genome-wide association studies, including PNPLA3, influence disease progression.

Genetic variation in the inflammation and innate immunity pathways and colorectal cancer risk

BACKGROUND

It is widely accepted that chronic inflammation plays a role in the etiology of colorectal cancer. Using a two-stage design, we examined the associations between colorectal cancer and common variation in 37 key genes in the inflammation and innate immunity pathways.

METHODS

In the discovery stage, 2,322 discordant sibships (2,535 cases, 3,915 sibling controls) from the Colorectal Cancer Family Registry were genotyped for more than 600 tagSNPs and 99 single-nucleotide polymorphisms (SNP) were selected for further examination based on strength of association. In the second stage, 351 SNPs tagging gene regions covered by the 99 SNPs were tested in 4,783 Multiethnic Cohort subjects (2,153 cases, 2,630 controls).

RESULTS

The association between rs9858822 in the PPARG gene and colorectal cancer was statistically significant at the end of the second stage (OR per allele = 1.36, Bonferroni-adjusted P = 0.045), based on the "effective" number of markers in stage II (n = 306). The risk allele C was common (frequency 0.3) in African Americans but rare (frequency < 0.03) in whites, Japanese Americans, Latinos, and Native Hawaiians. No statistically significant heterogeneity of effects across race/ethnicity, body mass index (BMI) levels, regular aspirin use, or pack-years of smoking was detected for this SNP. Suggestive associations were also observed for several SNPs in close vicinity to rs9858822.

CONCLUSIONS

Our results provide new evidence of association between PPARG variants and colorectal cancer risk.

IMPACT

Further replication in independent samples is warranted.

What is next after the genes for autoimmunity?

Clinical pathologies draw us to envisage disease as either an independent entity or a diverse set of traits governed by common physiopathological mechanisms, prompted by environmental assaults throughout life. Autoimmune diseases are not an exception, given they represent a diverse collection of diseases in terms of their demographic profile and primary clinical manifestations. Although they are pleiotropic outcomes of non-specific disease genes underlying similar immunogenetic mechanisms, research generally focuses on a single disease. Drastic technologic advances are leading research to organize clinical genomic multidisciplinary approaches to decipher the nature of human biological systems. Once the currently costly omic-based technologies become universally accessible, the way will be paved for a cleaner picture to risk quantification, prevention, prognosis and diagnosis, allowing us to clearly define better phenotypes always ensuring the integrity of the individuals studied. However, making accurate predictions for most autoimmune diseases is an ambitious challenge, since the understanding of these pathologies is far from complete. Herein, some pitfalls and challenges of the genetics of autoimmune diseases are reviewed, and an approximation to the future of research in this field is presented.

Metagenomic predictions: from microbiome to complex health and environmental phenotypes in humans and cattle

Mammals have a large cohort of endo- and ecto- symbiotic microorganisms (the microbiome) that potentially influence host phenotypes. There have been numerous exploratory studies of these symbiotic organisms in humans and other animals, often with the aim of relating the microbiome to a complex phenotype such as body mass index (BMI) or disease state. Here, we describe an efficient methodology for predicting complex traits from quantitative microbiome profiles. The method was demonstrated by predicting inflammatory bowel disease (IBD) status and BMI from human microbiome data, and enteric greenhouse gas production from dairy cattle rumen microbiome profiles. The method uses unassembled massively parallel sequencing (MPS) data to form metagenomic relationship matrices (analogous to genomic relationship matrices used in genomic predictions) to predict IBD, BMI and methane production phenotypes with useful accuracies (r = 0.423, 0.422 and 0.466 respectively). Our results show that microbiome profiles derived from MPS can be used to predict complex phenotypes of the host. Although the number of biological replicates used here limits the accuracy that can be achieved, preliminary results suggest this approach may surpass current prediction accuracies that are based on the host genome. This is especially likely for traits that are largely influenced by the gut microbiota, for example digestive tract disorders or metabolic functions such as enteric methane production in cattle.

A Monte Carlo permutation test for random mating using genome sequences

Testing for random mating of a population is important in population genetics, because deviations from randomness of mating may indicate inbreeding, population stratification, natural selection, or sampling bias. However, current methods use only observed numbers of genotypes and alleles, and do not take advantage of the fact that the advent of sequencing technology provides an opportunity to investigate this topic in unprecedented detail. To address this opportunity, a novel statistical test for random mating is required in population genomics studies for which large sequencing datasets are generally available. Here, we propose a Monte-Carlo-based-permutation test (MCP) as an approach to detect random mating. Computer simulations used to evaluate the performance of the permutation test indicate that its type I error is well controlled and that its statistical power is greater than that of the commonly used chi-square test (CHI). Our simulation study shows the power of our test is greater for datasets characterized by lower levels of migration between subpopulations. In addition, test power increases with increasing recombination rate, sample size, and divergence time of subpopulations. For populations exhibiting limited migration and having average levels of population divergence, the statistical power approaches 1 for sequences longer than 1Mbp and for samples of 400 individuals or more. Taken together, our results suggest that our permutation test is a valuable tool to detect random mating of populations, especially in population genomics studies.

Segregation of a latent high adiposity phenotype in families with a history of type 2 diabetes mellitus implicates rare obesity-susceptibility genetic variants with large effects in diabetes-related obesity

Background

We recently reported significantly greater weight gain in non-diabetic healthy subjects with a 1^st degree family history (FH+) of type 2 diabetes mellitus (T2DM) than in a matched control group without such history (FH−) during voluntary overfeeding, implying co-inheritance of susceptibilities to T2DM and obesity. We have estimated the extent and mode of inheritance of susceptibility to increased adiposity in FH+.

Methods

Normoglycaemic participants were categorised either FH+ (≥1 1^st degree relative with T2DM, 50F/30M, age 45±14 (SD) yr) or FH− (71F/51M, age 43±14 yr). Log-transformed anthropometric measurements (height, hip and waist circumferences) and lean, bone and fat mass (Dual Energy X-ray Absorptiometry) data were analysed by rotated Factor Analysis. The age- and gender-adjusted distributions of indices of adiposity in FH+ were assessed by fits to a bimodal model and by relative risk ratios (RR, FH+/FH−) and interpreted in a purely genetic model of FH effects.

Results

The two orthogonal factors extracted, interpretable as Frame and Adiposity accounted for 80% of the variance in the input data. FH+ was associated with significantly higher Adiposity scores (p<0.01) without affecting Frame scores. Adiposity scores in FH+ conformed to a bimodal normal distribution, consistent with dominant expression of major susceptibility genes with 59% (95% CI 40%, 74%) of individuals under the higher mode. Calculated risk allele frequencies were 0.09 (0.02, 0.23) in FH−, 0.36 (0.22, 0.48) in FH+ and 0.62 (0.36, 0.88) in unobserved T2DM-affected family members.

Conclusions

The segregation of Adiposity in T2DM-affected families is consistent with dominant expression of rare risk variants with major effects, which are expressed in over half of FH+ and which can account for most T2DM-associated obesity in our population. The calculated risk allele frequency in FH− suggests that rare genetic variants could also account for a substantial fraction of the prevalent obesity in this society.

GStream: improving SNP and CNV coverage on genome-wide association studies

We present GStream, a method that combines genome-wide SNP and CNV genotyping in the Illumina microarray platform with unprecedented accuracy. This new method outperforms previous well-established SNP genotyping software. More importantly, the CNV calling algorithm of GStream dramatically improves the results obtained by previous state-of-the-art methods and yields an accuracy that is close to that obtained by purely CNV-oriented technologies like Comparative Genomic Hybridization (CGH). We demonstrate the superior performance of GStream using microarray data generated from HapMap samples. Using the reference CNV calls generated by the 1000 Genomes Project (1KGP) and well-known studies on whole genome CNV characterization based either on CGH or genotyping microarray technologies, we show that GStream can increase the number of reliably detected variants up to 25% compared to previously developed methods. Furthermore, the increased genome coverage provided by GStream allows the discovery of CNVs in close linkage disequilibrium with SNPs, previously associated with disease risk in published Genome-Wide Association Studies (GWAS). These results could provide important insights into the biological mechanism underlying the detected disease risk association. With GStream, large-scale GWAS will not only benefit from the combined genotyping of SNPs and CNVs at an unprecedented accuracy, but will also take advantage of the computational efficiency of the method.

PUMA: a unified framework for penalized multiple regression analysis of GWAS data

Penalized Multiple Regression (PMR) can be used to discover novel disease associations in GWAS datasets. In practice, proposed PMR methods have not been able to identify well-supported associations in GWAS that are undetectable by standard association tests and thus these methods are not widely applied. Here, we present a combined algorithmic and heuristic framework for PUMA (Penalized Unified Multiple-locus Association) analysis that solves the problems of previously proposed methods including computational speed, poor performance on genome-scale simulated data, and identification of too many associations for real data to be biologically plausible. The framework includes a new minorize-maximization (MM) algorithm for generalized linear models (GLM) combined with heuristic model selection and testing methods for identification of robust associations. The PUMA framework implements the penalized maximum likelihood penalties previously proposed for GWAS analysis (i.e. Lasso, Adaptive Lasso, NEG, MCP), as well as a penalty that has not been previously applied to GWAS (i.e. LOG). Using simulations that closely mirror real GWAS data, we show that our framework has high performance and reliably increases power to detect weak associations, while existing PMR methods can perform worse than single marker testing in overall performance. To demonstrate the empirical value of PUMA, we analyzed GWAS data for type 1 diabetes, Crohns's disease, and rheumatoid arthritis, three autoimmune diseases from the original Wellcome Trust Case Control Consortium. Our analysis replicates known associations for these diseases and we discover novel etiologically relevant susceptibility loci that are invisible to standard single marker tests, including six novel associations implicating genes involved in pancreatic function, insulin pathways and immune-cell function in type 1 diabetes; three novel associations implicating genes in pro- and anti-inflammatory pathways in Crohn's disease; and one novel association implicating a gene involved in apoptosis pathways in rheumatoid arthritis. We provide software for applying our PUMA analysis framework.

Progress in multiple sclerosis genetics

A genetic component in the susceptibility to multiple sclerosis (MS) has long been known, and the first and major genetic risk factor, the HLA region, was identified in the 1970’s. However, only with the advent of genome-wide association studies in the past five years did the list of risk factors for MS grow from 1 to over 50. In this review, we summarize the search for MS risk genes and the latest results. Comparison with data from other autoimmune and neurological diseases and from animal models indicates parallels and differences between diseases. We discuss how these translate into an improved understanding of disease mechanisms, and address current challenges such as genotype-phenotype correlations, functional mechanisms of risk variants and the missing heritability.

The study of candidate genes related to the neurodevelopmental hypothesis of anorexia nervosa: classical association study versus decision tree

In this research, we conducted a study of genes connected with the neurodevelopmental hypothesis of anorexia nervosa, using classical statistical and data-mining methods to establish a relationship with disease risk and algorithms to identify the best genetic predictors of anorexia nervosa.