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BACKGROUND Indexes to quantify adherence to recommended dietary patterns have been developed for Western populations, but it is unclear whether these indexes can predict acute myocardial infarction (AMI) in Asian populations. OBJECTIVES We aimed to investigate the association between the Alternative Healthy Eating Index (AHEI)-2010 and risk of AMI and to evaluate potential mediation by traditional cardiovascular risk factors in a Chinese population. METHODS A nested case-control study in 751 incident cases of AMI (564 nonfatal and 288 fatal) and 1443 matched controls was conducted within the prospective Singapore Chinese Health Study, a cohort of ethnic Chinese men and women aged 45-75 y. At baseline, habitual diet was assessed by using a validated, semiquantitative food-frequency questionnaire. AMI cases were ascertained via linkage with nationwide hospital databases (confirmed through medical record review) and the Singapore Birth and Death Registry. We evaluated the association between the AHEI-2010 and cardiovascular risk factors, including glycated hemoglobin, high-sensitivity C-reactive protein, creatinine, plasma lipids (LDL and HDL cholesterol, triglycerides), and blood pressure. ORs and 95% CIs were computed by using multivariable-adjusted conditional logistic regression models. RESULTS Higher AHEI-2010 scores were associated with a lower risk of AMI (OR for the highest quartile compared with the lowest quartile: 0.62; 95% CI: 0.47, 0.81; P-trend < 0.001), with similar associations for fatal (OR: 0.60; 95% CI: 0.39, 0.94; P-trend = 0.009) and nonfatal (OR: 0.59; 95% CI: 0.43, 0.81; P-trend = 0.002) AMI. This association was only slightly attenuated after adjustment for potential biological intermediates (OR: 0.64; 95% CI: 0.48, 0.86; P-trend = 0.003). CONCLUSIONS Adherence to dietary recommendations as reflected in the AHEI-2010 was associated with a substantially lower risk of fatal and nonfatal AMI in an Asian population, and this association was largely independent of traditional cardiovascular risk factors.

Iron deficiency is associated with significant morbidity and mortality, can present with or without haematological changes and is a major cause of microcytic anaemia. In South Africa and Africa in general, there is a paucity of studies on the iron status of healthy adult non pregnant females and males18years of age. The aim of the study was to determine the prevalence of iron deficiency in a healthy South African population.A total of 651 healthy adults18years were included in the study. Blood samples were taken for the determination of iron status, haematological and inflammatory parameters. A ferritin level of30μg/L was used to define iron deficiency and these subjects were further divided into those with and without anaemia. Diet and menstrual history in females was further investigated.Overall, the prevalence of anaemia was 12.6% and iron deficiency was found in 78% of anaemic subjects. The prevalence of iron deficiency was 39.8% in all participants and females and Black Africans had a very high prevalence of 56.6% and 50.7% respectively. Significant (p0.05) differences were found in concentrations of ferritin, haemoglobin, iron, transferrin, transferrin saturation, MCV and MCH between the groups.Anaemia is a minor health problem but a large proportion of subjects with iron deficiency do not present with anaemia. The prevalence of iron deficiency was high especially in females and Black African participants.

The study of de novo point mutations (new germline mutations arising from the gametes of the parents) remained largely static until the arrival of next-generation sequencing technologies, which made both whole-exome sequencing (WES) and whole-genome sequencing (WGS) feasible in practical terms. Single nucleotide polymorphism genotyping arrays have been used to identify de novo copy-number variants in a number of common neurodevelopmental conditions such as schizophrenia and autism. By contrast, as point mutations and microlesions occurring de novo are refractory to analysis by these microarray-based methods, little was known about either their frequency or impact upon neurodevelopmental disease, until the advent of WES. De novo point mutations have recently been implicated in schizophrenia, autism and mental retardation through the WES of case-parent trios. Taken together, these findings strengthen the hypothesis that the occurrence of de novo mutations could account for the high prevalence of such diseases that are associated with a marked reduction in fecundity. De novo point mutations are also known to be responsible for many sporadic cases of rare dominant mendelian disorders such as Kabuki syndrome, Schinzel-Giedion syndrome and Bohring-Opitz syndrome. These disorders share a common feature in that they are all characterized by intellectual disability. In summary, recent WES studies of neurodevelopmental and neuropsychiatric disease have provided new insights into the role of de novo mutations in these disorders. Our knowledge of de novo mutations is likely to be further accelerated by WGS. However, the collection of case-parent trios will be a prerequisite for such studies. This review aims to discuss recent developments in the study of de novo mutations made possible by technological advances in DNA sequencing.

The advent of next-generation sequencing technologies has revolutionized the study of genetic variation in the human genome. Whole-genome sequencing currently represents the most comprehensive strategy for variant detection genome-wide but is costly for large sample sizes, and variants detected in noncoding regions remain largely uninterpretable. By contrast, whole-exome sequencing has been widely applied in the identification of germline mutations underlying Mendelian disorders, somatic mutations in various cancers and de novo mutations in neurodevelopmental disorders. Since whole-exome sequencing focuses upon the entire set of exons in the genome (the exome), it requires additional exome-enrichment steps compared with whole-genome sequencing. Although the availability of multiple commercial exome-enrichment kits has made whole-exome sequencing technically feasible, it has also added to the overall cost. This has led to the emergence of transcriptome (or RNA) sequencing as a potential alternative approach to variant detection within protein coding regions, since the transcriptome of a given tissue represents a quasi-complete set of transcribed genes (mRNAs) and other noncoding RNAs. A further advantage of this approach is that it bypasses the need for exome enrichment. Here we discuss the relative merits and limitations of these approaches as they are applied in the context of variant detection within gene coding regions.

Endothelial dysfunction plays an important role in development and progression of atherosclerosis and may also contribute to the pathogenesis of type 2 diabetes. This review summarizes recent findings on the effects of vitamin D, antioxidant vitamins, polyphenols, polyphenol-rich foods, dietary component combinations and healthy diets on endothelial function.Dietary patterns rich in fruit, vegetables, fish and nuts appear to have beneficial effects on endothelial function. With regard to specific foods, cacao and green tea consumption have been associated with improvement in endothelial function and this seems to be due to their flavan-3-ol (catechins and epigallocatechin gallate) content. The evidence for beneficial effects of other foods such as citrus fruit, apples and red wine is less consistent. Recent studies have also suggested beneficial effects of vitamin D and anthocyanins on endothelial function and have provided more insight into potential mechanisms underlying the effect of diet on endothelial function.The currently available evidence supports beneficial effects of various dietary compounds on endothelial function. However, in order to obtain strong evidence for relevant health effects that can be used for specific dietary recommendations, more long-term studies using well characterized diets/supplements in a large number of individuals are needed.

The potential applications of next-generation sequencing technologies in diagnostic laboratories have become increasingly evident despite the various technical challenges that still need to be overcome to potentiate its widespread adoption in a clinical setting. Whole-genome sequencing is now both technically feasible and 'cost effective' using next-generation sequencing techniques. However, this approach is still considered to be 'expensive' for a diagnostic test. Although the goal of the US$1000 genome is fast approaching, neither the analytical hurdles nor the ethical issues involved are trivial. In addition, the cost of data analysis and storage has been much higher than initially expected. As a result, it is widely perceived that targeted sequencing and whole-exome sequencing are more likely to be adopted as diagnostic tools in the foreseeable future. However, the information-generating power of whole-exome sequencing has also sparked considerable debate in relation to its deployment in genetic diagnostics, particularly with reference to the revelation of incidental findings. In this review, we focus on the targeted sequencing approach and its potential as a genetic diagnostic tool.

Recent developments in high-throughput sequence capture methods and next-generation sequencing technologies have now made exome sequencing a viable approach to elucidate the genetic basis of Mendelian disorders with hitherto unknown etiology. In addition, exome sequencing is increasingly being employed as a diagnostic tool for specific genetic diseases, particularly in the context of those disorders characterized by significant genetic and phenotypic heterogeneity, for example, Charcot-Marie-Tooth disease and congenital disorders of glycosylation. Such disorders are challenging to interrogate with conventional polymerase chain reaction–Sanger sequencing methods, because of the inherent difficulty in prioritizing candidate genes for diagnostic testing. Here, we explore the value of exome sequencing as a diagnostic tool and discuss whether exome sequencing can come to serve a dual role in diagnosis and discovery. We summarize the current status of exome sequencing, the technical challenges facing it, and its adaptation to diagnostics, and make recommendations for the use of exome sequencing as a routine diagnostic tool. Finally, we discuss pertinent ethical concerns, such as the use of exome sequencing data, originally generated in a diagnostic context, in research investigations.

The genomes of outbred populations were first shown in 2006 to contain regions of homozygosity (ROHs) of several megabases. Further studies have also investigated the characteristics of ROHs in healthy individuals in various populations but there are no studies on Singapore populations to date. This study aims to identify and investigate the characteristics of ROHs in three Singapore populations. A total of 268 samples (96 Chinese, 89 Malays and 83 Indians) are genotyped on Illumina Human 1 M Beadchip and Affymetrix Genome-Wide Human SNP Array 6.0. We use the PennCNV algorithm to detect ROHs. We report an abundance of ROHs (≥500 kb), with an average of more than one hundred regions per individual. On average, the Indian population has the lowest number of ROHs and smallest total length of ROHs per individual compared with the Chinese and Malay populations. We further investigate the relationship between the occurrence of ROHs and haplotype frequency, regional linkage disequilibrium (LD) and positive selection. Based on the results of this data set, we find that the frequency of occurrence of ROHs is positively associated with haplotype frequency and regional LD. The majority of regions detected for recent positive selection and regions with differential LD between populations overlap with the ROH loci. When we consider both the location of the ROHs and the allelic form of the ROHs, we are able to separate the populations by principal component analysis, demonstrating that ROHs contain information on population structure and the demographic history of a population.

The abundance of copy number variants (CNVs) and regions of homozygosity (ROHs) have been well documented in previous studies. In addition, their roles in complex diseases and traits have since been increasingly appreciated. However, only a limited amount of CNV and ROH data is currently available for the Swedish population. We conducted a population-based study to detect and characterize CNVs and ROHs in 87 randomly selected healthy Swedish individuals using the Affymetrix SNP Array 6.0. More than 600 CNV loci were detected in the population using two different CNV-detection algorithms (PennCNV and Birdsuite). A total of 196 loci were consistently identified by both algorithms, suggesting their reliability. Numerous disease-associated and pharmacogenetics-related genes were found to be overlapping with common CNV loci such as CFHR1/R3, LCE3B/3C, UGT2B17 and GSTT1. Correlation analysis between copy number polymorphisms (CNPs) and genome-wide association studies-identified single-nucleotide polymorphisms also indicates the potential roles of several CNPs as causal variants for diseases and traits such as body mass index, Crohn's disease and multiple sclerosis. In addition, we also identified a total of 14 815 ROHs 500 kb or 2814 ROHs 1M in the Swedish individuals with an average of 170 and 32 regions detected per individual respectively. Approximately 141 Mb or 4.92% of the genome is homozygous in each individual of the Swedish population. This is the first population-based study to investigate the population characteristics of CNVs and ROHs in the Swedish population. This study found many CNV loci that warrant further investigation, and also highlighted the abundance and importance of investigating ROHs for their associations with complex diseases and traits.

Over the past several years, more focus has been placed on dissecting the genetic basis of complex diseases and traits through genome-wide association studies. In contrast, Mendelian disorders have received little attention mainly due to the lack of newer and more powerful methods to study these disorders. Linkage studies have previously been the main tool to elucidate the genetics of Mendelian disorders; however, extremely rare disorders or sporadic cases caused by de novo variants are not amendable to this study design. Exome sequencing has now become technically feasible and more cost-effective due to the recent advances in high-throughput sequence capture methods and next-generation sequencing technologies which have offered new opportunities for Mendelian disorder research. Exome sequencing has been swiftly applied to the discovery of new causal variants and candidate genes for a number of Mendelian disorders such as Kabuki syndrome, Miller syndrome and Fowler syndrome. In addition, de novo variants were also identified for sporadic cases, which would have not been possible without exome sequencing. Although exome sequencing has been proven to be a promising approach to study Mendelian disorders, several shortcomings of this method must be noted, such as the inability to capture regulatory or evolutionary conserved sequences in non-coding regions and the incomplete capturing of all exons.

In western populations, high-sensitivity C-reactive protein (hsCRP), and to a lesser degree serum creatinine and haemoglobin A1c, predict risk of coronary heart disease (CHD). However, data on Asian populations that are increasingly affected by CHD are sparse and it is not clear whether these biomarkers can be used to improve CHD risk classification.We conducted a nested case-control study within the Singapore Chinese Health Study cohort, with incident 'hard' CHD (myocardial infarction or CHD death) as an outcome. We used data from 965 men (298 cases, 667 controls) and 528 women (143 cases, 385 controls) to examine the utility of hsCRP, serum creatinine and haemoglobin A1c in improving the prediction of CHD risk over and above traditional risk factors for CHD included in the ATP III model. For each sex, the performance of models with only traditional risk factors used in the ATP III model was compared with models with the biomarkers added using weighted Cox proportional hazards analysis. The impact of adding these biomarkers was assessed using the net reclassification improvement index.For men, loge hsCRP (hazard ratio 1.25, 95% confidence interval: 1.05; 1.49) and loge serum creatinine (hazard ratio 4.82, 95% confidence interval: 2.10; 11.04) showed statistically significantly associations with CHD risk when added to the ATP III model. We did not observe a significant association between loge haemoglobin A1c and CHD risk (hazard ratio 1.83, 95% confidence interval: 0.21; 16.06). Adding hsCRP and serum creatinine to the ATP III model improved risk classification in men with a net gain of 6.3% of cases (p-value = 0.001) being reclassified to a higher risk category, while it did not significantly reduce the accuracy of classification for non-cases. For women, squared hsCRP was borderline significantly (hazard ratio 1.01, 95% confidence interval: 1.00; 1.03) and squared serum creatinine was significantly (hazard ratio 1.81, 95% confidence interval: 1.49; 2.21) associated with CHD risk. However, the association between squared haemoglobin A1c and CHD risk was not significant (hazard ratio 1.05, 95% confidence interval: 0.99; 1.12). The addition of hsCRP and serum creatinine to the ATP III model resulted in 3.7% of future cases being reclassified to a higher risk category (p-value = 0.025), while it did not significantly reduce the accuracy of classification for non-cases.Adding hsCRP and serum creatinine, but not haemoglobin A1c, to traditional risk factors improved CHD risk prediction among non-diabetic Singaporean Chinese. The improved risk estimates will allow better identification of individuals at high risk of CHD than existing risk calculators such as the ATP III model.

Background. Studies of electrophoresis testing (serum protein electrophoresis (SPE), urine protein electrophoresis (UPE), immunofixation electrophoresis (IFE)) in a South African (SA) pathology laboratory setting are limited. Objectives. To evaluate the prevalence, testing pattern and yield of electrophoresis tests performed over a 5-year period in a tertiary academic laboratory and to relate these findings to bone marrow biopsy findings in a few selected cases. Methods. This was a retrospective audit of all SPE, UPE and IFE tests performed on new and follow-up adult patients (aged ≥18 years) from 2010 to 2015, using data from the Tygerberg Academic Hospital (Cape Town, SA) National Health Laboratory Service hospital information system database. A subgroup analysis of all patients with negative serum (SIFE) and/or urine immunofixation (UIFE) tests who had concurrent bone marrow biopsies close to the time of IFE testing was also performed. Results. A total of 5 086 SPE tests were performed (44.3% were follow-up tests, and of these patients 13.8% had SIFE tests); 1 299 UPE tests were performed (23.3% were follow-up tests, and of these patients 33.6% had UIFE tests). The mean ages of patients who had SIFE and UIFE tests were 59 years (standard deviation (SD) 14.2) and 60 years (SD 15), respectively. The female-to-male ratio was 1.1:1 for both SIFE and UIFE. The negative test yields for SIFE and UIFE were 31.3% and 52.1%, respectively. Bone marrow biopsy findings for patients with negative SIFE tests identified 8 out of the 20 biopsies (40.0%) as positive for myeloma. Conclusion. This audit provides baseline data on the prevalence of test requests, their source and the yield of electrophoresis testing in our laboratory. An increasing trend in SIFE and UIFE was evident.

Substantial progress has been made in human genetics and genomics research over the past ten years since the publication of the draft sequence of the human genome in 2001. Findings emanating directly from the Human Genome Project, together with those from follow-on studies, have had an enormous impact on our understanding of the architecture and function of the human genome. Major developments have been made in cataloguing genetic variation, the International HapMap Project, and with respect to advances in genotyping technologies. These developments are vital for the emergence of genome-wide association studies in the investigation of complex diseases and traits. In parallel, the advent of high-throughput sequencing technologies has ushered in the 'personal genome sequencing' era for both normal and cancer genomes, and made possible large-scale genome sequencing studies such as the 1000 Genomes Project and the International Cancer Genome Consortium. The high-throughput sequencing and sequence-capture technologies are also providing new opportunities to study Mendelian disorders through exome sequencing and whole-genome sequencing. This paper reviews these major developments in human genetics and genomics over the past decade.

The advances in next generation sequencing (NGS) technologies have had a significant impact on epigenomic research. The arrival of NGS technologies has enabled a more powerful sequencing based method--that is, ChIP-Seq--to interrogate whole genome histone modifications, improving on the conventional microarray based method (ChIP-chip). Similarly, the first human DNA methylome was mapped using NGS technologies. More importantly, studies of DNA methylation and histone modification using NGS technologies have yielded new discoveries and improved our knowledge of human biology and diseases. The concept that cytosine methylation was restricted to CpG dinucleotides has only been recently challenged by new data generated from sequencing the DNA methylome. Approximately 25% of all cytosine methylation identified in stem cells was in a non-CG context. The non-CG methylation was more enriched in gene bodies and depleted in protein binding sites and enhancers. The recent developments of third generation sequencing technologies have shown promising results of directly sequencing methylated nucleotides and having the ability to differentiate between 5-methylcytosine and 5-hydroxymethylcytosine. The importance of 5-hydroxymethylcytosine remains largely unknown, but it has been found in various tissues. 5-hydroxymethylcytosine was particularly enriched at promoters and in intragenic regions (gene bodies) but was largely absent from non-gene regions in DNA from human brain frontal lobe tissue. The presence of 5-hydroxymethylcytosine in gene bodies was more positively correlated with gene expression levels. The importance of studying 5-methylcytosine and 5-hydroxymethylcytosine separately for their biological roles will become clearer when more efficient methods to distinguish them are available.

Copy number variations can be identified using newer genotyping arrays with higher single nucleotide polymorphisms (SNPs) density and copy number probes accompanied by newer algorithms. McCarroll et al. (2008) applied these to the HapMap II samples and identified 1316 copy number polymorphisms (CNPs). In our study, we applied the same approach to 859 samples from three Singapore populations and seven HapMap III populations. Approximately 50% of the 1291 autosomal CNPs were found to be polymorphic only in populations of non-African ancestry. Pairwise comparisons among the 10 populations showed substantial differences in the CNPs frequencies. Additionally, 698 CNPs showed significant differences with false discovery rate (FDR)

A new era of copy number variants (CNVs) discovery began when two separate studies, published concurrently in 2004, identified several hundred deletions and duplications in the human genome. Over the past several years, most of the CNV data were generated by microarrays. These methods have several shortcomings, such as the inability to detect copy-neutral variants (e.g. inversions and translocations), limited sensitivity to detect smaller CNVs and poor resolution in determining CNV breakpoints especially with lower resolution microarrays. A paradigm shift in the discovery of copy-neutral variants was attributed to the development of a sequencing-based method known as paired-end mapping. This method was first demonstrated to be powerful in detecting structural variants using next-generation sequencing technologies in 2007. Further studies have also leveraged an important feature of sequencing data, where several hundred million short sequence reads are produced by next-generation sequencers, to detect CNVs based on the abundance or density of the sequence reads aligned to a reference genome. This approach is known as depth-of-coverage. These emerging sequencing-based methods will continue playing an important role in the discovery of structural variants until de novo genome assembly becomes more feasible. Key Concepts: A new era of copy number variants (CNVs) discovery began when two separate studies, published concurrently in 2004, identified several hundred deletions and duplications in the human genome. Both the sample size and the resolution of microarray are critical factors in determining the discovery of less common and smaller CNVs. ‘Human Genetic Variation’ was recognised as the ‘Breakthrough of The Year’ in 2007 by the journal Science. Other types of chromosomal rearrangements, particularly inversions and balanced translocations, have received relatively less attention. Inversions and translocations are also known as ‘copy-neutral variants’ or ‘balanced chromosomal rearrangements’ and do not involve changes in copies number. Collectively these copy number and copy-neutral variants are broadly classified as ‘structural variants’. The paradigm shift in the discovery of copy-neutral variants was attributed to the development of the paired-end mapping (PEM) method and concurrent advances in next-generation sequencing technologies. Further studies have also leveraged on an important feature of next-generation sequencing data where several hundred million short sequence reads are produced to detect CNVs based on the density of the sequence reads aligning to the reference genome, and this approach is known as depth-of-coverage (DOC). Although the PEM and DOC methods have overcome the major shortcomings of microarrays in detecting structural variants, these methods have their own weaknesses. The emerging sequencing-based methods (PEM and DOC) will continue to play a role in the discovery of structural variants until de novo genome assembly is more feasible Keywords: next-generation sequencing technologies; structural variants; paired-end mapping; depth-of-coverage; mate-pair mapping

The recent advances in high-throughput sequencing technologies have enabled several whole cancer genomes to be sequenced. In addition, a number of large-scale targeted resequencing studies have also been performed previously using Sanger sequencing methods. These studies have identified numerous somatic mutations in cancer genomes and provided new insights into the patterns of mutations in different cancer types. Several challenges remain in cancer genome sequencing such as accurately detecting different types of somatic mutations, the difficulty in identifying driver mutations, bioinformatics and analytical challenges in analysing the sequencing data and the cost of whole genome resequencing restricting the studies to a few genomes. However, cancer genome sequencing will eventually emerge as a routine tool to dissect the cancer genomes especially with the arrival of third generation sequencing technologies. The cancer genome resequencing studies have so far produced encouraging results to stimulate further studies to sequence more cancer genomes. These studies have made a significant contribution to the understanding of the somatic mutational profile of various cancers. Key Concepts: The genetic alterations of cancer occurring at the DNA sequence level can be classified as germline or somatic. Somatic mutations can occur in the cancer genome in several different forms such as single and double nucleotide variants or base substitutions, small insertion–deletions (indels) and larger structural chromosomal alterations. The recent advances in dissecting the somatic mutational profile of cancer genomes have been driven by high-throughput or next-generation sequencing (NGS) technologies which have enabled several whole cancer genomes to be sequenced for the first time. The involvement of somatic mutations in cancer initiation and progression, in addition to germline variations, is well recognised. Cancer genomes are characterised by their genomic instability which results in the occurrence of numerous somatic mutations which has proved challenging to investigate. Although a large number of somatic mutations have been detected in cancer genomes, only a small subset is predicted to be ‘driver’ mutations and the remainder considered ‘passenger’ mutations. Driver mutations are the mutations that initiate and drive oncogenesis steps, such as cell proliferation, tumour growth, angiogenesis, tissue invasion and metastasis. Several challenges remain in cancer genome sequencing such as to accurately detect different types of somatic mutations, the difficulty in identifying driver mutations, bioinformatics and analytical challenges and the cost for whole genome resequencing has restricted the studies to a few genomes. Currently there are no major obstacles in cataloging somatic mutations in cancer genomes. The real challenge lies in data interpretation and how the data can be used to discover new drugs or molecular markers for clinical applications. The ultimate goals of cancer genome sequencing are to improve the clinical management of patients and the creation of personalised medicine through the development of new therapeutic agents which are tailored to the individual based on their genetic information. Keywords: cancer genome; somatic mutation; driver mutation; whole genome resequencing; next generation sequencing technologies

Regions of homozygosity (ROHs) are more abundant in the human genome than previously thought. These regions are without heterozygosity, i.e. all the genetic variations within the regions have two identical alleles. At present there are no standardized criteria for defining the ROHs resulting in the different studies using their own criteria in the analysis of homozygosity. Compared to the era of genotyping microsatellite markers, the advent of high-density single nucleotide polymorphism genotyping arrays has provided an unparalleled opportunity to comprehensively detect these regions in the whole genome in different populations. Several studies have identified ROHs which were associated with complex phenotypes such as schizophrenia, late-onset of Alzheimer's disease and height. Collectively, these studies have conclusively shown the abundance of ROHs larger than 1 Mb in outbred populations. The homozygosity association approach holds great promise in identifying genetic susceptibility loci harboring recessive variants for complex diseases and traits.

In the more than 100 genome wide association studies (GWAS) conducted in the past 5 years, more than 250 genetic loci contributing to more than 40 common diseases and traits have been identified. Whilst many genes have been linked to a trait, both their individual and combined effects are small and unable to explain earlier estimates of heritability. Given the rapid changes in disease incidence that cannot be accounted for by changes in diagnostic practises, there is need to have well characterized exposure information in addition to genomic data for the study of gene-environment interactions. The case-control and cohort study designs are most suited for studying associations between risk factors and occurrence of an outcome. However, the case control study design is subject to several biases and hence the preferred choice of the prospective cohort study design in investigating gene-environment interactions. A major limitation of utilising the prospective cohort study design is the long duration of follow-up of participants to accumulate adequate outcome data. The GWAS paradigm is a timely reminder for traditional epidemiologists who often perform one- or few-at-a-time hypothesis-testing studies with the main hallmarks of GWAS being the agnostic approach and the massive dataset derived through large-scale international collaborations.