Bayes factors in complex genetics

WITHDRAWN: Genetics of Parkinson's disease

The Publisher regrets that this article is an accidental duplication of an article that has already been published, DOI of original article: https://doi.org/10.1016/j.mcp.2016.11.001. The duplicate article has therefore been withdrawn. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.

Transethnic associations among immune-mediated diseases and single-nucleotide polymorphisms of the aryl hydrocarbon response gene ARNT and the PTPN22 immune regulatory gene

BACKGROUND

Because immune responses are sensitive to environmental changes that drive selection of genetic variants, we hypothesized that polymorphisms of some xenobiotic response and immune response genes may be associated with specific types of immune-mediated diseases (IMD), while others may be associated with IMD as a larger category regardless of specific phenotype or ethnicity.

OBJECTIVE

To examine transethnic gene-IMD associations for single nucleotide polymorphism (SNP) frequencies of prototypic xenobiotic response genes-aryl hydrocarbon receptor (AHR), AHR nuclear translocator (ARNT), AHR repressor (AHRR) - and a prototypic immune response gene, protein tyrosine phosphatase, non-receptor type 22 (PTPN22), in subjects from the Environmental Polymorphisms Registry (EPR).

METHODS

Subjects (n = 3731) were genotyped for 14 SNPs associated with functional variants of the AHR, ARNT, AHRR, and PTPN22 genes, and their frequencies were compared among African Americans (n = 1562), Caucasians (n = 1838), and Hispanics (n = 331) with previously reported data. Of those genotyped, 2015 EPR subjects completed a Health and Exposure survey. SNPs were assessed via PLINK for associations with IMD, which included those with autoimmune diseases, allergic disorders, asthma, or idiopathic pulmonary fibrosis. Transethnic meta-analyses were performed using METAL and MANTRA approaches.

RESULTS

ARNT SNP rs11204735 was significantly associated with autoimmune disease by transethnic meta-analyses using METAL (odds ratio, OR [95% confidence interval] = 1.29 [1.08-1.55]) and MANTRA (ORs ranged from 1.29 to 1.30), whereas ARNT SNP rs1889740 showed a significant association with autoimmune disease by METAL (OR = 1.25 [1.06-1.47]). For Caucasian females, PTPN22 SNP rs2476601 was significantly associated with autoimmune disease by allelic association tests (OR = 1.99, [1.30-3.04]). In Caucasians and Caucasian males, PTPN22 SNP rs3811021 was significantly associated with IMD (OR = 1.39 [1.12-1.72] and 1.50 [1.12-2.02], respectively) and allergic disease (OR = 1.39 [1.12-1.71], and 1.62 [1.19-2.20], respectively). In the transethnic meta-analysis, PTPN22 SNP rs3811021 was significantly implicated in IMD by METAL (OR = 1.31 [1.10-1.56]), and both METAL and MANTRA suggested that rs3811021 was associated with IMD and allergic disease in males across all three ethnic groups (IMD METAL OR = 1.50 [1.15-1.95]; IMD MANTRA ORs ranged from 1.47 to 1.50; allergic disease METAL OR = 1.58 [1.20-2.08]; allergic disease MANTRA ORs ranged from 1.55 to 1.59).

CONCLUSIONS

Some xenobiotic and immune response gene polymorphisms were shown here, for the first time, to have associations across a broad spectrum of IMD and ethnicities. Our findings also suggest a role for ARNT in the development of autoimmune diseases, implicating environmental factors metabolized by this pathway in pathogenesis. Further studies are needed to confirm these data, assess the implications of these findings, define gene-environment interactions, and explore the mechanisms leading to these increasingly prevalent disorders.

External Replication of Urinary Bladder Cancer Prognostic Polymorphisms in the UK Biobank

Introduction: Multiple studies have reported genetic associations with prognostic outcomes of urinary bladder cancer. However, the lack of replication of these associations prohibits establishing further evidence-based research directions. Moreover, there is a lack of independent bladder cancer patient samples that contain prognostic measures, making genetic replication analyses even more challenging.

Materials and Methods: We have identified 1,534 eligible patients and used data on Hospital Episode Statistics in the UK Biobank to model variables of otherwise non-collected events on bladder cancer recurrence and progression. Data on survival was extracted from the Death Registry. We have used SNPTEST software to replicate previously reported genetic associations with bladder cancer recurrence (N = 69), progression (N = 23), survival (N = 53), and age at the time of diagnosis (N = 20).

Results: Using our algorithm, we have identified 618 recurrence and 58 UBC progression events. In total, there were 209 deaths (106 UBC-specific). In replication analyses, eight SNPs have reached nominal statistical significance (p < 0.05). Rs2042329 (CWC27) for UBC recurrence; rs804256, rs4639, and rs804276 (in/close to NEIL2) for NMIBC recurrence; rs2293347 (EGFR) for UBC OS; rs3756712 (PDCD6) for NMIBC OS; rs2344673 (RGS5) for MIBC OS, and rs2297518 (NOS2) for UBC progression. However, none have remained significant after adjustments for multiple comparisons.

Discussion: External replication in genetic epidemiology is an essential step to identify credible findings. In our study, we identify potential genetic targets of higher interest for UBC prognosis. In addition, we propose an algorithm for identifying UBC recurrence and progression using routinely-collected data on patient interventions.

On the Null Distribution of Bayes Factors in Linear Regression

We show that under the null, the 2 log(Bayes factor) is asymptotically distributed as a weighted sum of chi-squared random variables with a shifted mean. This claim holds for Bayesian multi-linear regression with a family of conjugate priors, namely, the normal-inverse-gamma prior, the g-prior, and the normal prior. Our results have three immediate impacts. First, we can compute analytically a p-value associated with a Bayes factor without the need of permutation. We provide a software package that can evaluate the p-value associated with Bayes factor efficiently and accurately. Second, the null distribution is illuminating to some intrinsic properties of Bayes factor, namely, how Bayes factor quantitatively depends on prior and the genesis of Bartlett's paradox. Third, enlightened by the null distribution of Bayes factor, we formulate a novel scaled Bayes factor that depends less on the prior and is immune to Bartlett's paradox. When two tests have an identical p-value, the test with a larger power tends to have a larger scaled Bayes factor, a desirable property that is missing for the (unscaled) Bayes factor.

[Epidemiology and causes of Parkinson's disease]

Parkinson's disease (PD) is the second most common neurodegenerative disease and has a growing socioeconomic impact due to demographic changes in the industrial nations. There are several forms of PD, a fraction of which (<5%) are monogenic, i. e. caused by mutations in single genes. At present, six genes have been established for the clinically classical form of parkinsonism including three autosomal dominantly (SNCA, LRRK2, VPS35) and three autosomal recessively inherited ones (Parkin, PINK1, DJ-1). In addition, there are a plethora of genes causing atypical forms of parkinsonism. In contrast, idiopathic PD is of a multifactorial nature. Genome-wide association studies have established a total of 26 genetic loci for this form of the disease; however, for most of these loci the underlying functional genetic variants have not yet been identified and the respective disease mechanisms remain unresolved. Furthermore, there are a number of environmental and life style factors that are associated with idiopathic PD. Exposure to pesticides and possibly a history of head trauma represent genuine risk factors. Other PD-associated factors, such as smoking and intake of coffee and alcohol may not represent risk factors per se and the cause-effect relationship has not yet been elucidated for most of these factors. A patient with a positive family history and/or an early age of disease onset should undergo counseling with respect to a possible monogenic form of the disease. Disease prediction based on genetic, environmental and life style factors is not yet possible for idiopathic PD and potential gene-specific therapies are currently in the development or early testing phase.

Genetics of Parkinson's disease

Almost two decades after the identification of SNCA as the first causative gene in Parkinson's disease (PD) and the subsequent understanding that genetic factors play a substantial role in PD development, our knowledge of the genetic architecture underlying this disease has vastly improved. Approximately 5-10% of patients suffer from a monogenic form of PD where autosomal dominant mutations in SNCA, LRRK2, and VPS35 and autosomal recessive mutations in PINK1, DJ-1, and Parkin cause the disease with high penetrance. Furthermore, recent whole-exome sequencing have described autosomal recessive DNAJC6 mutations in predominately atypical, but also cases with typical PD. In addition, several other genes have been linked to atypical Parkinsonian phenotypes. However, the vast majority of PD is genetically complex, i.e. it is caused by the combined action of common genetic variants in concert with environmental factors. By the application of genome-wide association studies, 26 PD risk loci have been established to date. Similar to other genetically complex diseases, these show only moderate effects on PD risk. Increasing this etiologic complexity, many of the involved genetic and environmental risk factors likely interact in an intricate fashion. This article aims to provide a comprehensive overview of the current knowledge in PD genetics.

Non-coding genomic regions possessing enhancer and silencer potential are associated with healthy aging and exceptional survival

We have completed a genome-wide linkage scan for healthy aging using data collected from a family study, followed by fine-mapping by association in a separate population, the first such attempt reported. The family cohort consisted of parents of age 90 or above and their children ranging in age from 50 to 80. As a quantitative measure of healthy aging, we used a frailty index, called FI34, based on 34 health and function variables. The linkage scan found a single significant linkage peak on chromosome 12. Using an independent cohort of unrelated nonagenarians, we carried out a fine-scale association mapping of the region suggestive of linkage and identified three sites associated with healthy aging. These healthy-aging sites (HASs) are located in intergenic regions at 12q13-14. HAS-1 has been previously associated with multiple diseases, and an enhancer was recently mapped and experimentally validated within the site. HAS-2 is a previously uncharacterized site possessing genomic features suggestive of enhancer activity. HAS-3 contains features associated with Polycomb repression. The HASs also contain variants associated with exceptional longevity, based on a separate analysis. Our results provide insight into functional genomic networks involving non-coding regulatory elements that are involved in healthy aging and longevity.

The role of TREM2 R47H as a risk factor for Alzheimer's disease, frontotemporal lobar degeneration, amyotrophic lateral sclerosis, and Parkinson's disease

A rare variant in TREM2 (p.R47H, rs75932628) was recently reported to increase the risk of Alzheimer's disease (AD) and, subsequently, other neurodegenerative diseases, i.e. frontotemporal lobar degeneration (FTLD), amyotrophic lateral sclerosis (ALS), and Parkinson's disease (PD). Here we comprehensively assessed TREM2 rs75932628 for association with these diseases in a total of 19,940 previously untyped subjects of European descent. These data were combined with those from 28 published data sets by meta-analysis. Furthermore, we tested whether rs75932628 shows association with amyloid beta (Aβ42) and total-tau protein levels in the cerebrospinal fluid (CSF) of 828 individuals with AD or mild cognitive impairment. Our data show that rs75932628 is highly significantly associated with the risk of AD across 24,086 AD cases and 148,993 controls of European descent (odds ratio or OR = 2.71, P = 4.67 × 10(-25)). No consistent evidence for association was found between this marker and the risk of FTLD (OR = 2.24, P = .0113 across 2673 cases/9283 controls), PD (OR = 1.36, P = .0767 across 8311 cases/79,938 controls) and ALS (OR = 1.41, P = .198 across 5544 cases/7072 controls). Furthermore, carriers of the rs75932628 risk allele showed significantly increased levels of CSF-total-tau (P = .0110) but not Aβ42 suggesting that TREM2's role in AD may involve tau dysfunction.

Statistical analysis for genome-wide association study

In the past few years, genome-wide association study (GWAS) has made great successes in identifying genetic susceptibility loci underlying many complex diseases and traits. The findings provide important genetic insights into understanding pathogenesis of diseases. In this paper, we present an overview of widely used approaches and strategies for analysis of GWAS, offered a general consideration to deal with GWAS data. The issues regarding data quality control, population structure, association analysis, multiple comparison and visual presentation of GWAS results are discussed; other advanced topics including the issue of missing heritability, meta-analysis, set-based association analysis, copy number variation analysis and GWAS cohort analysis are also briefly introduced.

No association between apolipoprotein E or N-acetyltransferase 2 gene polymorphisms and age-related hearing loss

OBJECTIVES/HYPOTHESIS

Age-related hearing loss has a genetic component, but there have been limited genetic studies in this field. Both N-acetyltransferase 2 and apolipoprotein E genes have previously been associated. However, these studies have either used small sample sizes, examined a limited number of polymorphisms, or have produced conflicting results. Here we use a haplotype tagging approach to determine association with age-related hearing loss and investigate epistasis between these two genes.

STUDY DESIGN

Candidate gene association study of a continuous phenotype.

METHODS

We investigated haplotype tagging single nucleotide polymorphisms in the N-acetyltransferase 2 gene and the presence/absence of the apolipoprotein E ε4 allele for association with age-related hearing loss in a cohort of 265 Caucasian elderly volunteers from Greater Manchester, United Kingdom. Hearing phenotypes were generated using principal component analysis of the hearing threshold levels for the better ear (severity, slope, and concavity). Genotype data for the N-acetyltransferase 2 gene was obtained from existing genome-wide association study data from the Illumina 610-Quadv1 chip. Apolipoprotein E genotyping was performed using Sequenom technology. Linear regression analysis was performed using Plink and Stata software.

RESULTS

No significant associations (P value, > 0.05) were observed between the N-acetyltransferase 2 or apolipoprotein E gene polymorphisms and any hearing factor. No significant association was observed for epistasis analysis of apolipoprotein E ε4 and the N-acetyltransferase 2 single nucleotide polymorphism rs1799930 (NAT2*6A).

CONCLUSION

We found no evidence to support that either N-acetyltransferase 2 or apolipoprotein E gene polymorphisms are associated with age-related hearing loss in a cohort of 265 elderly volunteers.

Trans-ethnic meta-analysis of white blood cell phenotypes

White blood cell (WBC) count is a common clinical measure used as a predictor of certain aspects of human health, including immunity and infection status. WBC count is also a complex trait that varies among individuals and ancestry groups. Differences in linkage disequilibrium structure and heterogeneity in allelic effects are expected to play a role in the associations observed between populations. Prior genome-wide association study (GWAS) meta-analyses have identified genomic loci associated with WBC and its subtypes, but much of the heritability of these phenotypes remains unexplained. Using GWAS summary statistics for over 50 000 individuals from three diverse populations (Japanese, African-American and European ancestry), a Bayesian model methodology was employed to account for heterogeneity between ancestry groups. This approach was used to perform a trans-ethnic meta-analysis of total WBC, neutrophil and monocyte counts. Ten previously known associations were replicated and six new loci were identified, including several regions harboring genes related to inflammation and immune cell function. Ninety-five percent credible interval regions were calculated to narrow the association signals and fine-map the putatively causal variants within loci. Finally, a conditional analysis was performed on the most significant SNPs identified by the trans-ethnic meta-analysis (MA), and nine secondary signals within loci previously associated with WBC or its subtypes were identified. This work illustrates the potential of trans-ethnic analysis and ascribes a critical role to multi-ethnic cohorts and consortia in exploring complex phenotypes with respect to variants that lie outside the European-biased GWAS pool.

Multiple sclerosis genetics

Familial aggregation and the studies of twins indicate that heredity contributes to multiple sclerosis (MS) risk. Immunologic studies of leukocyte antigens subsequently followed by gene-mapping techniques identified the primary MS susceptibility locus to be within the major histocompatibility complex (MHC). The primary risk allele is HLA-DRB1*15, although other alleles of this gene also influence MS susceptibility. Other genes within the MHC also contribute to MS susceptibility. Genome-wide association studies have identified over 50 additional common variants of genes across the genome. Estimates suggest that there may be as many as 200 genes involved in MS susceptibility. In addition to these common polymorphisms, studies have identified several rare risk alleles in some families. Interestingly, the majority of the genes identified have known immunologic functions and many contribute to the risk of inheriting other autoimmune diseases. Genetic variants in the vitamin D metabolic pathway have also been identified. That vitamin D contributes to MS susceptibility as both an environmental as well as genetic risk factor underscores the importance of this metabolic pathway in disease pathogenesis. Current efforts are focused on understanding how the myriad of genetic risk alleles interact within networks to influence MS risk at family level as well as within populations.

Genetic Associations of Angiotensin-Converting Enzyme with Primary Intracerebral Hemorrhage: A Meta-analysis

Background

A number of studies have reported an association of angiotensin-converting enzyme (ACE) gene polymorphism with primary intracerebral hemorrhage (PICH), however the reports have demonstrated inconclusive results. To clarify this conflict, we updated the previously performed meta-analysis by Peck et al., which revealed negative results, by investigating the ACE polymorphism and its correlation to PICH.

Methods

PubMed and Embase databases (through Dec 2012) were searched for English articles on the relationship of the I/D polymorphism in ACE with PICH in humans. Summary odds ratios (ORs) were estimated and potential sources of heterogeneity and bias were explored.

Results

A total of 805 PICH cases and 1641 control cases obtained from 8 case-control studies were included. The results suggest that in dominant genetic models, the ACE I/D polymorphic variant was associated with a 58% increase in susceptibility risk of PICH (OR = 1.58; 95% CI = 1.07–2.35 for DD vs. DI+II). However, in the subgroup analysis based on race, a significant increased risk was found in Asian DD homozygote carriers (OR = 1.76 and 95% CI = 1.16–2.66 for DD vs. DI+II), but not in Caucasian DD homozygote carriers (OR = 1.18, 95% CI = 0.36–3.88, P = 0.784 for DD vs. DI+II). The heterogeneity between studies was remarkable, and its major sources of heterogeneity were due to the year in which the study was published. No potential publication bias was observed in dominant genetic models.

Conclusions

These data demonstrated evidence of a positive association between ACE I/D polymorphism with PICH, and suggested that the ACE gene is a PICH susceptible gene in Asian populations.

Naturally occurring variation in the Glutathione-S-Transferase 4 gene determines neurodegeneration after traumatic brain injury

AIM

Genetic factors are important for outcome after traumatic brain injury (TBI), although exact knowledge of relevant genes/pathways is still lacking. We here used an unbiased approach to define differentially activated pathways between the inbred DA and PVG rat strains. The results prompted us to study further if a naturally occurring genetic variation in glutathione-S-transferase alpha 4 (Gsta4) affects the outcome after TBI.

RESULTS

Survival of neurons after experimental TBI is increased in PVG compared to the DA strain. Global expression profiling analysis shows the glutathione metabolism pathway to be the most regulated between the strains, with increased Gsta4 in PVG among top regulated transcripts. A congenic strain (R5) with a PVG genomic insert containing the Gsta4 gene on DA background displays a reversal of the strain pattern for Gsta4 expression and increased survival of neurons compared to DA. Gsta4 is known to effectively reduce 4-hydroxynonenal (4-HNE), a noxious by-product of lipid peroxidation. Immunostaining of 4-HNE was evident in both rat and human TBI. Intracerebral injection of 4-HNE resulted in neurodegeneration with increased levels of a marker for nerve injury in cerebrospinal fluid of DA compared to R5.

INNOVATION

These findings provide strong support for the notion that the inherent capability of coping with increased 4-HNE after TBI affects outcome in terms of nerve cell loss.

CONCLUSION

A naturally occurring variation in Gsta4 expression in rats affects neurodegeneration after TBI. Further studies are needed to explore if genetic variability in Gsta4 can be associated to outcome also in human TBI.

The genetics of multiple sclerosis: an up-to-date review

Multiple sclerosis (MS) is a prevalent inflammatory disease of the central nervous system that often leads to disability in young adults. Treatment options are limited and often only partly effective. The disease is likely caused by a complex interaction between multiple genes and environmental factors, leading to inflammatory-mediated central nervous system deterioration. A series of genomic studies have confirmed a central role for the immune system in the development of MS, including genetic association studies that have now dramatically expanded the roster of MS susceptibility genes beyond the longstanding human leukocyte antigen (HLA) association in MS first identified nearly 40 years ago. Advances in technology together with novel models for collaboration across research groups have enabled the discovery of more than 50 non-HLA genetic risk factors associated with MS. However, with a large proportion of the disease heritability still unaccounted for, current studies are now geared towards identification of causal alleles, associated pathways, epigenetic mechanisms, and gene-environment interactions. This article reviews recent efforts in addressing the genetics of MS and the challenges posed by an ever increasing amount of analyzable data, which is spearheading development of novel statistical methods necessary to cope with such complexity.

Association between insertion/deletion polymorphism in angiotensin-converting enzyme gene and acute lung injury/acute respiratory distress syndrome: a meta-analysis

BACKGROUND

A previous meta-analysis reported a positive association between an insertion/deletion (I/D) polymorphism in the angiotensin-converting enzyme gene (ACE) and the risk of acute lung injury (ALI)/acute respiratory distress syndrome (ARDS). Here, we updated this meta-analysis and additionally assessed the association of this polymorphism with ALI/ARDS mortality.

METHODS

We searched electronic databases through October 2011 for the terms "angiotensin-converting enzyme gene", "acute lung injury", and "acute respiratory distress syndrome," and reviewed all studies that reported the relationship of the I/D polymorphism in ACE with ALI/ARDS in humans. Seven studies met the inclusion criteria, comprising 532 ALI/ARDS patients, 3032 healthy controls, and 1432 patients without ALI/ARDS. We used three genetic models: the allele, dominant, and recessive models.

RESULTS

The ACE I/D polymorphism was not associated with susceptibility to ALI/ARDS for any genetic model. However, the ACE I/D polymorphism was associated with the mortality risk of ALI/ARDS in Asian subjects ( P(allele) < 0.0001, P(dominant) = 0.001, P(recessive) = 0.002). This finding remained significant after correction for multiple comparisons.

CONCLUSIONS

There is a possible association between the ACE I/D polymorphism genotype and the mortality risk of ALI/ARDS in Asians.

The genetics of multiple sclerosis: an up-to-date review

Multiple sclerosis (MS) is a prevalent inflammatory disease of the central nervous system that often leads to disability in young adults. Treatment options are limited and often only partly effective. The disease is likely caused by a complex interaction between multiple genes and environmental factors, leading to inflammatory-mediated central nervous system deterioration. A series of genomic studies have confirmed a central role for the immune system in the development of MS, including genetic association studies that have now dramatically expanded the roster of MS susceptibility genes beyond the longstanding human leukocyte antigen (HLA) association in MS first identified nearly 40 years ago. Advances in technology together with novel models for collaboration across research groups have enabled the discovery of more than 50 non-HLA genetic risk factors associated with MS. However, with a large proportion of the disease heritability still unaccounted for, current studies are now geared towards identification of causal alleles, associated pathways, epigenetic mechanisms, and gene-environment interactions. This article reviews recent efforts in addressing the genetics of MS and the challenges posed by an ever increasing amount of analyzable data, which is spearheading development of novel statistical methods necessary to cope with such complexity.

Bayes factor based on the trend test incorporating Hardy-Weinberg disequilibrium: more power to detect genetic association

In the analysis of case-control genetic association, the trend test and Pearson's test are the two most commonly used tests. In genome-wide association studies (GWAS), Bayes factor (BF) is a useful tool to support significant P-values, and a better measure than P-value when results are compared across studies with different sample sizes. When reporting the P-value of the trend test, we propose a BF directly based on the trend test. To improve the power to detect association under recessive or dominant genetic models, we propose a BF based on the trend test and incorporating Hardy-Weinberg disequilibrium in cases. When the true model is unknown, or both the trend test and Pearson's test or other robust tests are applied in genome-wide scans, we propose a joint BF, combining the previous two BFs. All three BFs studied in this paper have closed forms and are easy to compute without integrations, so they can be reported along with P-values, especially in GWAS. We discuss how to use each of them and how to specify priors. Simulation studies and applications to three GWAS are provided to illustrate their usefulness to detect nonadditive gene susceptibility in practice.

Discussion on common data analysis strategies used in MS-based proteomics

Current proteomics technology is limited in resolving the proteome complexity of biological systems. The main issue at stake is to increase throughput and spectra quality so that spatiotemporal dimensions, population parameters and the complexity of protein modifications on a quantitative scale can be considered. MS-based proteomics and protein arrays are the main players in large-scale proteome analysis and an integration of these two methodologies is powerful but presently not sufficient for detailed quantitative and spatiotemporal proteome characterization. Improvements of instrumentation for MS-based proteomics have been achieved recently resulting in data sets of approximately one million spectra which is a large step in the right direction. The corresponding raw data range from 50 to 100 Gb and are frequently made available. Multidimensional LC-MS data sets have been demonstrated to identify and quantitate 2000-8000 proteins from whole cell extracts. The analysis of the resulting data sets requires several steps from raw data processing, to database-dependent search, statistical evaluation of the search result, quantitative algorithms and statistical analysis of quantitative data. A large number of software tools have been proposed for the above-mentioned tasks. However, it is not the aim of this review to cover all software tools, but rather discuss common data analysis strategies used by various algorithms for each of the above-mentioned steps in a non-redundant approach and to argue that there are still some areas which need improvements.