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A review of study designs and statistical methods for genomic epidemiology studies using next generation sequencing.

Wang Q, Lu Q, Zhao H - Front Genet (2015)

Bottom Line: For example, although a large number of disease-associated loci have been identified from genome-wide association studies in the past 10 years, it is challenging to interpret these results as most disease-associated markers have no clear functional roles in disease etiology, and all the identified genomic factors only explain a small portion of disease heritability.Although the current scale of NGS studies is still limited due to the high cost, the success of several recent studies suggests the great potential for applying NGS in genomic epidemiology, especially as the cost of sequencing continues to drop.Finally, we highlight recent advancements in statistical methods proposed for sequencing analysis, including group-based association tests, meta-analysis techniques, and annotation tools for variant prioritization.

View Article: PubMed Central - PubMed

Affiliation: Program of Computational Biology and Bioinformatics, Yale University New Haven, CT, USA.

ABSTRACT
Results from numerous linkage and association studies have greatly deepened scientists' understanding of the genetic basis of many human diseases, yet some important questions remain unanswered. For example, although a large number of disease-associated loci have been identified from genome-wide association studies in the past 10 years, it is challenging to interpret these results as most disease-associated markers have no clear functional roles in disease etiology, and all the identified genomic factors only explain a small portion of disease heritability. With the help of next-generation sequencing (NGS), diverse types of genomic and epigenetic variations can be detected with high accuracy. More importantly, instead of using linkage disequilibrium to detect association signals based on a set of pre-set probes, NGS allows researchers to directly study all the variants in each individual, therefore promises opportunities for identifying functional variants and a more comprehensive dissection of disease heritability. Although the current scale of NGS studies is still limited due to the high cost, the success of several recent studies suggests the great potential for applying NGS in genomic epidemiology, especially as the cost of sequencing continues to drop. In this review, we discuss several pioneer applications of NGS, summarize scientific discoveries for rare and complex diseases, and compare various study designs including targeted sequencing and whole-genome sequencing using population-based and family-based cohorts. Finally, we highlight recent advancements in statistical methods proposed for sequencing analysis, including group-based association tests, meta-analysis techniques, and annotation tools for variant prioritization.

No MeSH data available.


Related in: MedlinePlus

Number of publications studying human traits using various techniques (1980–2014). Only the publications in core clinical journals or MEDLINE are included. The vertical axis indicates the number of publications and the horizontal axis indicates different years. The three colors correspond to genetic linkage studies, GWAS, and next generation sequencing, respectively.
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Figure 1: Number of publications studying human traits using various techniques (1980–2014). Only the publications in core clinical journals or MEDLINE are included. The vertical axis indicates the number of publications and the horizontal axis indicates different years. The three colors correspond to genetic linkage studies, GWAS, and next generation sequencing, respectively.

Mentions: The rapid advancement of biotechnology has brought paradigm shifts in genetic/genomic epidemiology. From linkage studies to genome-wide association studies (GWAS) to the extensive application of next-generation sequencing (NGS), technological developments have improved study designs, deepened our understanding of disease etiology, and led to numerous scientific discoveries (Figure 1). This can be seen in the study of Crohn’s disease, an inflammatory bowel disease with prevalence 0.32% in Europe and North America (Molodecky et al., 2012). Twin-based epidemiological analysis first suggested that there is a genetic component of Crohn’s disease (Molodecky et al., 2012); family-based linkage studies then identified six loci associated to the disease (Hugot et al., 1996; Cardinale et al., 2013); GWAS identified 163 loci at genome-wide significance level, which collectively explain 13.6% of the phenotypic variance (Duerr et al., 2006; Imielinski et al., 2009; Jostins et al., 2012); and re-sequencing GWAS loci identified several causal variants with low minor allele frequencies (Momozawa et al., 2011; Rivas et al., 2011; Cardinale et al., 2013; Ellinghaus et al., 2013; Hunt et al., 2013).


A review of study designs and statistical methods for genomic epidemiology studies using next generation sequencing.

Wang Q, Lu Q, Zhao H - Front Genet (2015)

Number of publications studying human traits using various techniques (1980–2014). Only the publications in core clinical journals or MEDLINE are included. The vertical axis indicates the number of publications and the horizontal axis indicates different years. The three colors correspond to genetic linkage studies, GWAS, and next generation sequencing, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4403555&req=5

Figure 1: Number of publications studying human traits using various techniques (1980–2014). Only the publications in core clinical journals or MEDLINE are included. The vertical axis indicates the number of publications and the horizontal axis indicates different years. The three colors correspond to genetic linkage studies, GWAS, and next generation sequencing, respectively.
Mentions: The rapid advancement of biotechnology has brought paradigm shifts in genetic/genomic epidemiology. From linkage studies to genome-wide association studies (GWAS) to the extensive application of next-generation sequencing (NGS), technological developments have improved study designs, deepened our understanding of disease etiology, and led to numerous scientific discoveries (Figure 1). This can be seen in the study of Crohn’s disease, an inflammatory bowel disease with prevalence 0.32% in Europe and North America (Molodecky et al., 2012). Twin-based epidemiological analysis first suggested that there is a genetic component of Crohn’s disease (Molodecky et al., 2012); family-based linkage studies then identified six loci associated to the disease (Hugot et al., 1996; Cardinale et al., 2013); GWAS identified 163 loci at genome-wide significance level, which collectively explain 13.6% of the phenotypic variance (Duerr et al., 2006; Imielinski et al., 2009; Jostins et al., 2012); and re-sequencing GWAS loci identified several causal variants with low minor allele frequencies (Momozawa et al., 2011; Rivas et al., 2011; Cardinale et al., 2013; Ellinghaus et al., 2013; Hunt et al., 2013).

Bottom Line: For example, although a large number of disease-associated loci have been identified from genome-wide association studies in the past 10 years, it is challenging to interpret these results as most disease-associated markers have no clear functional roles in disease etiology, and all the identified genomic factors only explain a small portion of disease heritability.Although the current scale of NGS studies is still limited due to the high cost, the success of several recent studies suggests the great potential for applying NGS in genomic epidemiology, especially as the cost of sequencing continues to drop.Finally, we highlight recent advancements in statistical methods proposed for sequencing analysis, including group-based association tests, meta-analysis techniques, and annotation tools for variant prioritization.

View Article: PubMed Central - PubMed

Affiliation: Program of Computational Biology and Bioinformatics, Yale University New Haven, CT, USA.

ABSTRACT
Results from numerous linkage and association studies have greatly deepened scientists' understanding of the genetic basis of many human diseases, yet some important questions remain unanswered. For example, although a large number of disease-associated loci have been identified from genome-wide association studies in the past 10 years, it is challenging to interpret these results as most disease-associated markers have no clear functional roles in disease etiology, and all the identified genomic factors only explain a small portion of disease heritability. With the help of next-generation sequencing (NGS), diverse types of genomic and epigenetic variations can be detected with high accuracy. More importantly, instead of using linkage disequilibrium to detect association signals based on a set of pre-set probes, NGS allows researchers to directly study all the variants in each individual, therefore promises opportunities for identifying functional variants and a more comprehensive dissection of disease heritability. Although the current scale of NGS studies is still limited due to the high cost, the success of several recent studies suggests the great potential for applying NGS in genomic epidemiology, especially as the cost of sequencing continues to drop. In this review, we discuss several pioneer applications of NGS, summarize scientific discoveries for rare and complex diseases, and compare various study designs including targeted sequencing and whole-genome sequencing using population-based and family-based cohorts. Finally, we highlight recent advancements in statistical methods proposed for sequencing analysis, including group-based association tests, meta-analysis techniques, and annotation tools for variant prioritization.

No MeSH data available.


Related in: MedlinePlus