Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases

May combine two claims.

RNA-Seq provides comprehensive information on mRNA abundance, alternative splicing, nucleotide variation, and structure alteration.

“RNA-Seq provides comprehensive information on mRNA abundance, alternative splicing, nucleotide variation, and structure alteration.”

• cites Ozsolak & Milos, 2011Not checked yet

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• cites Z. Wang et al., 2009 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

NGS can call SNP genotypes and structural variations and provides ultimate coverage and resolution of genetic variations, including private mutations.

“Similarly, NGS technology has been used to call SNP genotypes and structural variations and provides the ultimate coverage and resolution of genetic variations including private mutations of individuals.”

• cites Nielsen et al., 2011 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Thousands of genetic variants have been linked with hundreds of human traits and diseases.

“thousands of genetic variants have been linked with hundreds of human traits and diseases (Welter et al., 2014).”

• cites Welter et al., 2014 sourceNot checked yet

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May combine two claims.

Integrative multi-omic data may improve understanding of the molecular dynamics underlying disease pathophysiology and may lead to new strategies for early detection, prevention, and treatment.

“The integrative approach of multi-omic data may enhance the understanding of the molecular dynamics underlying the pathophysiology of diseases, and may lead to novel strategies for early detection, prevention and treatment of human diseases.”

May combine two claims.

Proteomics offers highly complementary information to genomics and can yield new biological insights into disease.

“Proteomics measures all proteins and peptides in biological samples, and offers highly complementary information to genomics. As many biological functions are transmitted through proteins, proteomics can yield new biology and insights into disease.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Next-generation sequencing provides the most complete genome-wide coverage for GWAS and transcriptomic studies.

“For both GWAS and transcriptomic studies, the next generation sequencing (NGS) technologies provide the most complete genome-wide coverage (Metzker, 2010).”

• cites Metzker, 2010 sourceNot checked yet

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Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Multi-omic studies provide a combined view of multiple functional layers at a system level and pave the road to precision medicine.

“The new multi-omic studies will provide a combined view of multiple functional layer at a system level, and pave the road to precision medicine”

May combine two claims.

Epigenetic modifications through DNA methylation and other mechanisms can regulate gene expression and exert a long-term impact on chronic disease development.

“Epigenetic modifications, through DNA methylation (DNAm) and other mechanisms, can regulate gene expression and exert a long-term impact on the development of chronic diseases.”

• cites Bird, 2007 sourceNot checked yet

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• cites Foley et al.Not checked yet

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May combine two claims.

DNA, RNA, protein, and metabolite have complementary roles and synergistic interactions that can only be captured by integrative study of multiple molecular layers.

“DNA, RNA, protein, and metabolite often have complementary roles to jointly perform a certain biological function. Such complementary effects and synergistic interactions between omic layers in the life-course can only be captured by integrative study of multiple molecular layers.”

Probably not a substantial claim: may not pass S4 (based).

GWAS cannot capture intra-individual changes over time and how such changes relate to disease risk.

“GWAS have successfully identified the genetic susceptibility of human diseases, however, it cannot capture the intra-individual changes over time and how such changes relate to the disease risk”

May combine two claims.

Each omics technology measures one type of biomolecule accurately and comprehensively, but by itself is limited by the functional roles of that molecule in a biological system.

“Although each omics technology is capable of measuring one type of biomolecule accurately and comprehensively, by themselves, they are all limited by the functional roles of each type of molecule in a biological system.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The 450K platform represents about 2% of all DNA methylation sites in the human genome and over-represents genic regions, including promoter, gene body, and 3'-UTR.

“On the down side, it only represents ~2% of all DNAm sites of the human genome, and over-represents the genic regions (75% of sites) including promoter, gene body and 3’-UTR (Sandoval et al., 2011).”

• cites Sandoval et al., 2011 sourceNot checked yet

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May combine two claims.

Epigenetic modifications are shaped by environmental exposures such as smoking and poor nutrition, by genetic factors, and by age.

“Epigenetic modifications are shaped by environmental (e.g. smoking (Breitling, Yang, Korn, Burwinkel, & Brenner, 2011; Shenker et al.; Sun, 2014; Sun, Smith, et al., 2013), poor nutrition(Waterland & Jirtle, 2003), genetic factors (Sun, 2014; D. Zhang et al., 2010), and age – all well known risk factors human diseases”

• cites Breitling et al., 2011 sourceNot checked yet

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• cites Waterland & Jirtle, 2003Not checked yet

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• cites Sun, 2014 sourceNot checked yet

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May combine two claims.

The Illumina 450K chip offers accurate and reproducible performance with known but adjustable bias between Infinium I and II assays.

“The 450K chip offers accurate and reproducible performance (Bibikova et al., 2011; Sandoval et al., 2011) with known but adjustable bias between Infinium I and II assays (Dedeurwaerder et al., 2011).”

• cites Bibikova et al., 2011 sourceNot checked yet

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• cites Sandoval et al., 2011 sourceNot checked yet

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• cites Dedeurwaerder et al., 2011 sourceNot checked yet

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May combine two claims.

Sequencing-based methods suffer from technical biases and variations in sample preparation, processing, and experimental procedures that may not be fully addressable in statistical analyses or require intensive bioinformatic/biostatistical analyses.

“But these sequencing-based methods suffer from unique technical biases and variations in sample preparation, processing and experimental procedures, which may not be fully addressable in the statistical analyses or require intensive bioinformatic/biostatistical analyses (Michels et al., 2013).”

• cites Michels et al., 2013 sourceNot checked yet

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May combine two claims.

Sequencing-based techniques provide better genomic coverage than the 450K array and can assess genetic variants and allele-specific methylation beyond preselected microarray probes.

“They provide better genomic coverage than 450K array, and can assess the genetic variants and allele-specific methylation beyond the preselected microarray probes.”

• cites Serre et al., 2010 sourceNot checked yet

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• cites Meissner et al., 2008 sourceNot checked yet

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• cites Y. Li et al., 2010Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Bisulfite conversion does not distinguish 5-methylcytosine from 5-hydroxymethylcytosine.

“This chemical conversion does not distinguish 5-methylcytosine (5mC) from 5-hydroxymethylcytosine (5hmC) (Jin, Kadam, & Pfeifer, 2010)”

• cites Jin et al., 2010 sourceNot checked yet

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May combine two claims.

Inflammatory markers are associated with epigenetics at the gene level in peripheral leukocytes, which play a critical role in acute and chronic inflammation related to the pathophysiology of many human diseases.

“Additionally, inflammatory markers have been associated with epigenetics at the gene level in peripheral leukocytes (Sun, Lazarus, et al., 2013; Uddin et al., 2011), which play a critical role in acute and chronic inflammation related to pathophysiology of many human diseases.”

• cites Sun, Lazarus, et al., 2013Not checked yet

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• cites Uddin et al., 2011 sourceNot checked yet

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Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

Omics-specific procedures for obtaining high-quality data are essential for the success of a multi-omics study.

“These omics-specific procedures for obtaining high-quality data are essential for the success of the multi-omics study.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

Proteomics can measure where and when proteins localize in the cell or tissue, which is important to understand disease and cannot be captured by other genomic technologies.

“Proteomics can also measure where and when proteins localize in the cell or tissue, that is important to understand the disease process but cannot be captured by other genomic technologies.”

May combine two claims.

Epigenetic modifications may not be sufficient to cause changes in gene expression; they potentiate gene expression changes conditional on other co-regulators.

“Although epigenetic markers can induce the transcriptional regulation, the epigenetic modification may not be sufficient to cause changes of gene expression levels. In other words, epigenetic modifications potentiate the gene expression changes conditional on other co-regulators.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Proteomics is positioned to define the functional roles of proteins in normal and disease-related cellular processes and to enable hypothesis-driven and discovery research of human diseases.

“Thus, proteomics is positioned to define the functional roles of proteins in normal and disease-related cellular processes, and to enable hypothesis-driven and discovery research of human diseases (Nilsson et al., 2010).”

• cites Nilsson et al., 2010 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The protein products of 17,294 genes were identified and mapped in the draft human proteome using 30 human samples of tissues and cells.

“Recently, the protein products of 17,294 genes were identified and mapped in the draft of human proteome using 30 human samples of tissues and cells (Kim et al., 2014).”

• cites Kim et al., 2014 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Mass spectrometry and protein separation allow rapid and accurate detection of hundreds of human proteins and peptides from a small amount of body fluid or tissue.

“The technological advance in mass spectrometry (MS) and protein separation now allows rapid and accurate detection of hundreds of human proteins and peptides from a small amount of body fluid or tissue (Kraemer et al., 2011).”

• cites Kraemer et al., 2011 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Individual proteins can span 10 orders of magnitude in abundance.

“Individual proteins can span 10 orders of magnitude in abundance (e.g. serum albumin and interleukin 6) (Anderson & Anderson, 2002).”

• cites Anderson & Anderson, 2002Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Proper procedures in sample collection, sample preparation, MS experiments, and data analysis are critical to obtain high-quality data for hypothesis-driven or proteome-wide discovery research.

“Proper procedures in sample collection, sample preparation, MS experiments and data analysis are all critical to obtain high-quality data for hypothesis-driven or proteome-wide discovery research (Nilsson et al., 2010).”

• cites Nilsson et al., 2010 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Numerous issues such as imperfect epityping technologies, limited specimen types, cell-type specificity, sample size, and data analysis framework need to be addressed and improved in EWAS.

“Despite these encouraging findings from the first wave of EWAS of disease traits, numerous issues such as imperfect epityping technologies, limited types of specimens from human subjects, cell-type specificity, sample size and data analysis framework need to be further addressed and improved (Heijmans & Mill, 2012).”

• cites Heijmans & Mill, 2012Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The draft proteome demonstrated the feasibility of building a complete human proteome encompassing over 200 cell types and all body fluids.

“This draft proteome demonstrated the feasibility of building a complete human proteome encompassing over 200 cell types and all body fluids.”

• cites Kim et al., 2014 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Highly abundant housekeeping proteins from 2,350 genes constitute approximately 75% of total protein mass, while low-abundance proteins constitute the majority of protein species in human.

“Although, highly abundant “housekeeping” proteins from 2,350 genes constitute approximately 75% of total protein mass, low-abundance proteins constitute the majority of the protein species in human (Kim et al., 2014).”

• cites Kim et al., 2014 sourceNot checked yet

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May combine two claims.

Blood as a surrogate tissue is sometimes biologically relevant, for example in autoimmune and inflammatory conditions, but its relevance for many diseases is not clear.

“Although the use of blood as surrogate tissue is sometimes relevant (e.g. autoimmune diseases and inflammatory processes), the biological relevance of blood-based omic profiles may not be apparent for many human diseases.”

Probably not a substantial claim: may not pass S4 (based). May combine two claims.

A tissue sample contains multiple cell types, and each cell type has its own omic profile.

“A tissue sample always involves several cell types, each having a unique omic profile.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Proteomics has been widely adopted in studies of human diseases including cancer, multiple sclerosis, and schizophrenia.

“Proteomics approach has been widely adopted in studies of human diseases including cancer (Frantzi et al., 2015; S. Pan, Brentnall, & Chen, 2015; Petricoin et al., 2002; Tsai et al., 2015), multiple sclerosis (Farias, Pradella, Schmitt, Santos, & Martins-de-Souza, 2014) and schizophrenia (Al Awam et al., 2015; Nascimento & Martins-de-Souza, 2015).”

• cites Frantzi et al., 2015 sourceNot checked yet

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• cites Farias et al., 2014 sourceNot checked yet

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• cites Al Awam et al., 2015 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Tissue and cell type specificity creates two problems for multi-omics studies: choosing tissues and cell types, and dealing with tissue heterogeneity.

“The tissue and cell type specificity leads to two important issues in multi-omics studies, selection of tissues and cell types, and heterogeneity of tissues.”

May combine two claims. The quote only partly states this claim.

A two-stage approach using mixed cell types adjusted for heterogeneity followed by sorted-cell study can identify relevant cell types without expensive profiling or large samples and can provide direct inference on disease molecular mechanism.

“An alternative approach is to conduct initial association study using a large sample of mixed cell types adjusted for the effect of heterogeneity. Once an averaged effect is identified, a follow up study of the sorted cells can focus on a specific omic maker to identify the most relevant cell types.”

• Also stated in: § 2.5 Common issues and limitations of omics approaches · plain

  “The analysis in the second stage does not require expensive omic profiling or large amount of samples, but provides direct inference on the molecular mechanism of a disease.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Key genes such as DNA methyltransferases directly control the DNA methylation profile.

“Key genes such as DNA methyltransferases (DNMTs) directly control the DNA methylation profile.”

May combine two claims.

Most GWAS findings map to non-coding regions, but a large proportion map to ENCODE regulatory elements, suggesting an important role for transcriptional regulation in human diseases.

“Most GWAS findings map to non-coding regions, but a large proportion map to ENCODE regulatory elements (Schaub, Boyle, Kundaje, Batzoglou, & Snyder, 2012), suggesting the important role of transcriptional regulation underlying human diseases.”

• cites Schaub, Boyle, Kundaje, Batzoglou, & Snyder, 2012Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Other genetic variants may influence DNA methylation patterns by modifying enzyme accessibility or binding affinity.

“Other genetic variants may also influence the patterns of DNA methylation by modifying the accessibility or binding affinity of enzymes.”

Probably not a substantial claim: may not pass S4 (based). May combine two claims.

Disease-associated genetic variants do not directly cause disease at the molecular level; they act through intermediate phenotypes that induce molecular and physiological changes.

“Disease-associated genetic variants do not directly cause disease at the molecular level. They affect intermediate phenotypes that in turn induce molecular and physiological changes.”

May combine two claims.

Identifying intermediate phenotypes directly influenced by genetic variants can provide functional information about disease-causing genes and pathways and reveal genetic-controlled molecular systems underlying health and disease.

“Thus, identifying the intermediate phenotypes of gene expression, DNA methylation, protein and metabolite levels that directly influence by genetic variants has the potential to provide the functional information of disease-causing genes and pathways, and to unravel the genetic-controlled molecular systems underlying the changes of health and disease status.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Several systems genetics studies of metabolites in human plasma or serum have been reported.

“Several systems genetics studies of metabolites in human plasma or serum have been reported (Gieger et al., 2008; Kettunen et al., 2012; Shin et al., 2014; Suhre et al., 2011; Yu et al., 2013).”

• cites Gieger et al., 2008 sourceNot checked yet

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• cites Kettunen et al., 2012 sourceNot checked yet

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• cites Shin et al., 2014 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The NIH Roadmap Epigenomics Consortium generated 111 human reference epigenomes for primary cells and tissues, the largest collection so far.

“The national institute of health Roadmap Epigenomics Consortium generated 111 human reference epigenomes for primary cells and tissues, the largest collection so far (Roadmap Epigenomics et al., 2015).”

• cites Roadmap Epigenomics et al., 2015 sourceNot checked yet

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May combine two claims.

Metabolites play critical roles in biological pathways and are partially controlled by genetic regulation.

“Metabolites play critical roles in biological pathways, and are partially controlled by genetic regulations.”

May combine two claims.

A population study of 8,330 European individuals analyzed 216 serum metabolites using NMR and identified 31 mQTLs, including 11 novel loci without known association with any traits or diseases.

“Another population study of 8,330 European individuals analyzed 216 serum metabolites using NMR (Kettunen et al., 2012). The GWAS of these metabolites identified 31 mQTLs including 11 novel loci without known association with any traits or diseases.”

• cites Kettunen et al., 2012 sourceNot checked yet

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May combine two claims.

Early pQTL studies suffered from inconsistent protein detection across samples and limited dynamic range for low-abundance proteins.

“Early pQTL studies suffered from an inconsistent detection of proteins across samples and a limited dynamic range for low abundance proteins (Foss et al., 2007).”

• cites Foss et al., 2007 sourceNot checked yet

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May combine two claims.

Levels of a set of metabolites are strongly associated with genetic loci, and some of these loci overlap with GWAS loci for disease traits.

“The levels of a set of metabolites are strongly associated with genetic loci, and some of these loci overlapped with GWAS loci for disease traits.”

May combine two claims.

Trans-meQTL analysis is more computationally intensive and needs a more stringent multiple-testing correction than cis-meQTL analysis.

“Because of the large number of SNP-DNA methylation site pairs to test, the trans-meQTL analysis is more computational intensive and requires a more stringent multiple-testing correction than the cis-meQTL analysis.”

Probably not a substantial claim: may not pass S3 (load-bearing).

MR uses a genetic variant that mimics the biological effects of a modifiable exposure.

“The MR approach uses the genetic variant mimicking the biological effects of a modifiable exposure.”

May combine two claims.

Significant GWAS loci are enriched for eQTLs and meQTLs.

“Significant GWAS loci are enriched for e QTLs (Nicolae et al., 2010) and meQTLs (X. Zhang et al., 2014).”

• cites Nicolae et al., 2010 sourceNot checked yet

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• cites X. Zhang et al., 2014 sourceNot checked yet

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May combine two claims.

Picotti et al. used a nearly complete yeast proteome and genetic variation data to identify strong genetic effects on protein abundance and to demonstrate epistatic interactions affecting protein levels.

“Picotti et al. used a nearly complete map of yeast proteome and genetic variation data to identify strong genetic effects of protein abundance, and to demonstrate epistatic interactions affecting protein levels (Picotti et al., 2013).”

• cites Picotti et al., 2013 sourceNot checked yet

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May combine two claims.

A pQTL analysis of mouse plasma identified strong genetic determinants for approximately 40% of tested proteins and suggested causal genetic variants affecting plasma protein abundance.

“The pQTL analysis of mouse plasma identified strong genetic determinants for approximately 40% of tested proteins, and suggested causal genetic variants affecting abundance of plasma proteins (Holdt et al., 2013).”

• cites Holdt et al., 2013 sourceNot checked yet

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May combine two claims.

Overall, QTL studies have catalogued many QTLs across multiple omic layers and tissues/cell types, providing a resource for understanding genetic regulation of intermediate phenotypes and molecular networks that mediate genetic-environment interaction in human diseases.

“Overall, these studies catalogued a large number of QTLs across multiple omic layers in multiple tissues and cell types, and provide a rich resource not only to understand the genetic regulation of intermediate phenotypes, but also to illustrate important molecular networks mediating the interaction between genetic variants and environment for human diseases.”

May combine two claims.

A GWAS of 42 proteins identified eight strong pQTLs with large effect sizes (0.19 to 0.69 standard deviations per allele), but the panel covered only a small fraction of the proteome.

“A GWAS of 42 proteins identified eight strong pQTLs with rather large effect sizes (0.19 to 0.69 standard deviations per allele). However, the panel of proteins only covered a small fraction of the proteome (Melzer et al., 2008).”

• cites Melzer et al., 2008 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

MR was initially proposed as an epidemiologic method to obtain unbiased estimates of putative causal effects without conducting a randomized trial.

“MR was initially proposed as an epidemiologic method to obtain unbiased estimates of the putative casual effects without conducting a randomized trial (Gray & Wheatley, 1991; Katan, 1986).”

• cites Gray & Wheatley, 1991Not checked yet

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• cites Katan, 1986 sourceNot checked yet

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May combine two claims.

QTLs have been used to infer functional links between genetic variants and disease traits in GWAS and have led to follow-up studies uncovering biological functions of disease-associated loci.

“First, these QTLs have been used to infer the functional link between genetic variants and disease traits in recent GWAS, and lead to follow-up studies uncovering the biological functions of disease-associated loci.”

May combine two claims.

When SNPs have no effect on gene expression, there is no indirect effect, so the null hypothesis is not equivalent to testing for no total effect but tests whether a joint effect of SNPs, expression, and possibly their interaction exists.

“When the SNPs have no effect on the gene expression (i.e., not eQTL SNPs; αG = 0), then there is no IE of the SNPs on Y, so that the null hypothesis (3) is not equivalent to testing for no TE, but simply whether there exists a joint effect of the SNPs, the gene expression, and possibly their interactive effect on the disease risk.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Regression-based joint modeling uses the mediation analysis framework and typically analyzes data collected on the same subjects.

“The regression-based approach jointly models multi-omics data, using the framework of mediation analysis. These data are typically collected on the same subjects.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Another type of multi-omics dataset consists of data collected on different sets of individuals from different studies.

“Another type of datasets is multi-omics data collected on different sets of individuals from different studies.”

Classified as probably not a substantial claim.

Both genetic and environmental factors contribute to the development of human diseases.

“Both genetic and environmental factors contribute to the development of human diseases.”

Probably not a substantial claim: may not pass S2 (checkable).

The multi-omics approach holds promise to advance human disease research.

“The multi-omics approach thus holds the promises to further advance human disease research.”

Probably not a substantial claim: may not pass S4 (based).

Different research questions can be answered for each type of multi-omic dataset using corresponding statistical approaches.

“Different research questions can be answered for each type of multi-omic dataset using corresponding statistical approaches.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Existing studies in humans and model organisms highlighted the complexity of genomic information flow and interactive networks in biological processes and disease development.

“Existing studies in human and model organisms highlighted the complexity of genomic information flow and the interactive networks in biological processes and disease development.”

Classified as probably not a substantial claim. May combine two claims.

A comparable high-throughput approach for studying environmental causes of human diseases remains unavailable, leaving a large proportion of phenotypic variance unexplained.

“On the other hand, a comparable high-throughput approach to studying the environmental causes of human diseases remains unavailable, which leaves a large proportion of the phenotypic variance unexplained.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

The ideal datasets for integrative analysis are multi-omics data all collected on the same set of samples.

“The ideal datasets for such an integrative analysis are multi-omics data all collected on the same set of samples.”

Probably not a substantial claim: may not pass S4 (based).

Non-genetic factors can cause important changes in proteins, nucleic acids, lipids and other biomolecules that have direct roles in biochemical and cellular functions.

“The non-genetic factors can cause important changes in proteins, nucleic acids, lipids and other biomolecules, which have direct roles in biochemical and cellular functions.”

Probably not a substantial claim: may not pass S4 (based). May combine two claims.

Multi-omics data all collected on the same samples are often not possible because of cost or because control samples lack appropriate tissues.

“However, this is often not possible because of the cost or because the control samples simply do not have the appropriate tissues to study.”

May combine two claims.

In GWAS, SNPs and disease outcomes are collected but gene expression and methylation are not; in QTL studies, SNPs, gene expression and methylation are collected but disease outcome is not.

“Specifically, in GWAS, SNPs and the disease outcomes are collected, but not gene expression/methylation; in QTL studies, SNPs, gene expression and methylation are collected, but not the disease outcome.”

May combine two claims.

If there is an effect of G on E, the indirect effect through expression corresponds to βE, βME, βGE, and βGME, and testing hypothesis (7) is equivalent to testing the indirect effect mediated through gene expression.

“If there exists an effect of G on E, ΔG→E→Y corresponds to βE, βME, βGE, and βGME; it means that the test of the hypothesis (7) is equivalent to the test of the IE of SNPs mediated through gene expression.”

May combine two claims.

The direct effect corresponds to βG, βGM, βGE, and βGME and is not influenced by the G-M-E relationship.

“For example, the DE ΔG→Y corresponds to βG, βGM, βGE, and βGME, which is not influenced by the relationship among G, M, and E.”

May combine two claims.

Zhao et al. (2014) considered the same omic datasets as Huang et al. (2014) but focused on testing the indirect effect of SNPs on disease outcome that is regulated by gene expression.

“Zhao et al. (2014) considered the same omic datasets that Huang et al. (2014) have dealt with, i.e., SNP, gene expression, and disease data collected on the same set of subjects. However, Zhao et al. (2014) focused on testing the IE of the SNPs on the disease outcome that is regulated by gene expression.”

• cites Zhao et al. (2014) sourceNot checked yet

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• cites Huang et al. (2014)Not checked yet

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Classified as probably not a substantial claim.

The meQTL and eQTL studies should be conducted on the same subjects in order to calculate μME.

“Note that the meQTL and eQTL studies should be conducted on the same subjects in order to calculate μME.”

May combine two claims.

Zhao et al.'s work is analogous to Huang et al. (2014) but focuses solely on increasing power of SNP association testing rather than assigning causal interpretations.

“This work is analogous to the work by Huang et al. (2014) but focuses solely on increasing the power of SNP association testing, rather than on assigning causal interpretations to any of the parameters.”

• cites Huang et al. (2014)Not checked yet

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May combine two claims.

The eQTLs of a gene constitute a unique genetic signature and should overlap significantly with the set of loci associated with disease.

“Thus, the eQTLs of the gene, which constitute a unique “genetic signature” of this gene, should overlap significantly with the set of loci associated with the disease.”

May combine two claims.

Although Uj and Vj are not observed, they are related to peQTL,j and pGWAS,j: small p-values make Uj or Vj likely to be 1.

“Although Uj and Vj are not observed, they are related to peQTL,j and pGWAS,j: when peQTL,j (pGWAS,j) is small, it is likely that Uj (Vj) = 1.”

Classified as probably not a substantial claim. May combine two claims.

To apply the method genome-wide, Zhao et al. proposed considering one gene in E at a time and restricting to cis SNPs to reduce the multiple testing burden.

“To apply their method in an agnostic, genome-wide manner, they proposed to consider one gene in E at a time; to reduce the multiple testing burden imposed by the huge number of pairwise tests they proposed to restrict to testing only those SNPs located cis to each gene.”

May combine two claims.

Zhao et al.'s model (9) differs from model (2) by not considering regulation of a SNP on individual gene expression but on a linear combination, requiring fewer parameters.

“Model (9) is significantly different from model (2) in that the former does not consider the regulation of the SNP on the expression of an individual gene, but on one particular linear combination of them; it hence requires estimating fewer parameters.”

Probably not a substantial claim: may not pass S3 (load-bearing).

When a particular gene set or pathway is of interest and the number of genes in E does not exceed the number of subjects, Zhao et al. proposed standard estimating equation theory for inference.

“When a particular set of genes or a pathway is of interest such that the number of genes in E does not exceed the number of subjects, Zhao et al. (2014) proposed to use the standard estimating equation theory for inference.”

• cites Zhao et al. (2014) sourceNot checked yet

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May combine two claims.

A phenotype-based permutation procedure that preserves LD structure in SNP data and gene-gene correlation structure in gene expression data can calculate FDR or FWER and declare significant gene sets controlling FDR or FWER below a threshold.

“Based on a phenotype-based permutation procedure that preserves LD structure in SNP data and gene-gene correlation structure in gene expression data, the false discovery rate (FDR) or the family-wise error rate (FWER) can be calculated and the significant gene sets are declared controlling for FDR or FWER below a certain threshold.”

• cites Xiong et al. (2012) sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The method has been implemented in a software program called Sherlock.

“It has been implemented in a software program called Sherlock.”

Probably not a substantial claim: may not pass S4 (based). May combine two claims.

Under the null, P(TeQTL,j | Uj = 0) and P(TGWAS,j | Vj = 0) follow the standard normal distribution.

“Under the null, P(TeQTL,j | Uj = 0) and P(TGWAS,j | Vj = 0) follow the standard normal distribution.”

Classified as probably not a substantial claim.

A simulation approach was proposed to compute the p-value of the Bayes factor for a gene.

“To assess the statistical significance of BF, a simulation approach was proposed to compute the p-value of the BF for a gene.”

Classified as probably not a substantial claim.

When Z = 1 and Uj = 1, Vj should always be 1, as a true eQTL of the gene is expected to be associated with disease.

“When Z = 1 and Uj = 1, Vj should always be 1, as a true eQTL of the gene is expected to be associated with the disease.”

• AssumptionThe authors state this as an assumption: In He et al.'s method, when Z = 1 and Uj = 1, Vj should always be 1, because a true eQTL of the gene is expected to be associated with disease.

Classified as probably not a substantial claim.

The weighted Kolmogorov-Smirnov statistic (gene set association score) determines whether genes in a gene set are preferentially near the top of a ranked list based on gene association scores.

“Third, the gene set is evaluated by a weighted Kolmogorov-Smirnov (K-S) statistic (i.e., gene set association score) to determine whether the genes belonging to this gene set are preferentially near the top of the ranked ordered list based on gene association scores.”

• cites Xiong et al. (2012) sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

In GSAA, gene expression data and SNP genotype data are allowed to be collected on the same samples or on different samples.

“The gene expression data and the SNP genotype data are allowed to be collected on the same samples or different samples.”

Classified as probably not a substantial claim. May combine two claims.

When Z = 0, the gene is irrelevant to disease and Uj and Vj are independent.

“When Z = 0, the gene is irrelevant to the disease and thus Uj and Vj are independent.”

May combine two claims.

When Z = 1 and Uj = 0, the SNP is not an eQTL and Uj and Vj are independent.

“When Z = 1 and Uj =0, this SNP is not an eQTL and thus Uj and Vj are also independent.”