Low-level APC mutational mosaicism is the underlying cause in a substantial fraction of unexplained colorectal adenomatous polyposis cases.

BACKGROUND: In 30-50% of patients with colorectal adenomatous polyposis, no germline mutation in the known genes APC, causing familial adenomatous polyposis, MUTYH, causing MUTYH-associated polyposis, or POLE or POLD1, causing polymerase-proofreading-associated polyposis can be identified, although a hereditary aetiology is likely. This study aimed to explore the impact of APC mutational mosaicism in unexplained polyposis. METHODS: To comprehensively screen for somatic low-level APC mosaicism, high-coverage next-generation sequencing of the APC gene was performed using DNA from leucocytes and a total of 53 colorectal tumours from 20 unrelated patients with unexplained sporadic adenomatous polyposis. APC mosaicism was assumed if the same loss-of-function APC mutation was present in ≥ 2 anatomically separated colorectal adenomas/carcinomas per patient. All mutations were validated using diverse methods. RESULTS: In 25% (5/20) of patients, somatic mosaicism of a pathogenic APC mutation was identified as underlying cause of the disease. In 2/5 cases, the mosaic level in leucocyte DNA was slightly below the sensitivity threshold of Sanger sequencing; while in 3/5 cases, the allelic fraction was either very low (0.1-1%) or no mutations were detectable. The majority of mosaic mutations were located outside the somatic mutation cluster region of the gene. CONCLUSIONS: The present data indicate a high prevalence of pathogenic mosaic APC mutations below the detection thresholds of routine diagnostics in adenomatous polyposis, even if high-coverage sequencing of leucocyte DNA alone is taken into account. This has important implications for both routine work-up and strategies to identify new causative genes in this patient group.

Exome sequencing characterizes the somatic mutation spectrum of early serrated lesions in a patient with serrated polyposis syndrome (SPS).

BACKGROUND: Serrated or Hyperplastic Polyposis Syndrome (SPS, HPS) is a yet poorly defined colorectal cancer (CRC) predisposition characterised by the occurrence of multiple and/or large serrated polyps throughout the colon. A serrated polyp-CRC sequence (serrated pathway) of CRC formation has been postulated, however, to date only few molecular signatures of serrated neoplasia (BRAF, KRAS, RNF43 mutations, CpG Island Methylation, MSI) have been described in a subset of SPS patients and neither the etiology of the syndrome nor the distinct genetic alterations during tumorigenesis have been identified. METHODS: To identify somatic point mutations in potential novel candidate genes of SPS-associated lesions and the involved pathways we performed exome sequencing of eleven early serrated polyps obtained from a 41 year-old female patient with clinically confirmed SPS. For data filtering and analysis, standard pipelines were used. Somatic mutations were identified by comparison with leukocyte DNA and were validated by Sanger sequencing. RESULTS: The BRAF p.V600E or KRAS p.G12D mutation was identified in six polyps (~50%) and not found in polyps from the distal colon. In addition, we found seven unique rare somatic alterations of seven different genes in four serrated tumours, all of which are missense variants. The variant in ABI3BP and CATSPERB are predicted to be deleterious. No established cancer gene or candidate genes related to serrated tumorigenesis were affected. CONCLUSIONS: Somatic mutations seem to be rare events in early hyperplastic and serrated lesions of SPS patients. Neither frequently affected genes nor enrichment of specific pathways were observed. Thus, other alterations such as non-coding variants or epigenetic changes might be the major driving force of tumour progression in SPS.

SUCLG2 identified as both a determinator of CSF Aß1-42 levels and an attenuator of cognitive decline in Alzheimer's disease.

Cerebrospinal fluid amyloid-beta 1-42 (Aß1-42) and phosphorylated Tau at position 181 (pTau181) are biomarkers of Alzheimer's disease (AD). We performed an analysis and meta-analysis of genome-wide association study data on Aß1-42 and pTau181 in AD dementia patients followed by independent replication. An association was found between Aß1-42 level and a single-nucleotide polymorphism in SUCLG2 (rs62256378) (P = 2.5×10(-12)). An interaction between APOE genotype and rs62256378 was detected (P = 9.5 × 10(-5)), with the strongest effect being observed in APOE-ε4 noncarriers. Clinically, rs62256378 was associated with rate of cognitive decline in AD dementia patients (P = 3.1 × 10(-3)). Functional microglia experiments showed that SUCLG2 was involved in clearance of Aß1-42.

METAINTER: meta-analysis of multiple regression models in genome-wide association studies.

MOTIVATION: Meta-analysis of summary statistics is an essential approach to guarantee the success of genome-wide association studies (GWAS). Application of the fixed or random effects model to single-marker association tests is a standard practice. More complex methods of meta-analysis involving multiple parameters have not been used frequently, a gap that could be explained by the lack of a respective meta-analysis pipeline. Meta-analysis based on combining p-values can be applied to any association test. However, to be powerful, meta-analysis methods for high-dimensional models should incorporate additional information such as study-specific properties of parameter estimates, their effect directions, standard errors and covariance structure. RESULTS: We modified 'method for the synthesis of linear regression slopes' recently proposed in the educational sciences to the case of multiple logistic regression, and implemented it in a meta-analysis tool called METAINTER. The software handles models with an arbitrary number of parameters, and can directly be applied to analyze the results of single-SNP tests, global haplotype tests, tests for and under gene-gene or gene-environment interaction. Via simulations for two-single nucleotide polymorphisms (SNP) models we have shown that the proposed meta-analysis method has correct type I error rate. Moreover, power estimates come close to that of the joint analysis of the entire sample. We conducted a real data analysis of six GWAS of type 2 diabetes, available from dbGaP (http://www.ncbi.nlm.nih.gov/gap). For each study, a genome-wide interaction analysis of all SNP pairs was performed by logistic regression tests. The results were then meta-analyzed with METAINTER. AVAILABILITY: The software is freely available and distributed under the conditions specified on http://metainter.meb.uni-bonn.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Novel genetic matching methods for handling population stratification in genome-wide association studies.

BACKGROUND: A usually confronted problem in association studies is the occurrence of population stratification. In this work, we propose a novel framework to consider population matchings in the contexts of genome-wide and sequencing association studies. We employ pairwise and groupwise optimal case-control matchings and present an agglomerative hierarchical clustering, both based on a genetic similarity score matrix. In order to ensure that the resulting matches obtained from the matching algorithm capture correctly the population structure, we propose and discuss two stratum validation methods. We also invent a decisive extension to the Cochran-Armitage Trend test to explicitly take into account the particular population structure. RESULTS: We assess our framework by simulations of genotype data under the null hypothesis, to affirm that it correctly controls for the type-1 error rate. By a power study we evaluate that structured association testing using our framework displays reasonable power. We compare our result with those obtained from a logistic regression model with principal component covariates. Using the principal components approaches we also find a possible false-positive association to Alzheimer's disease, which is neither supported by our new methods, nor by the results of a most recent large meta analysis or by a mixed model approach. CONCLUSIONS: Matching methods provide an alternative handling of confounding due to population stratification for statistical tests for which covariates are hard to model. As a benchmark, we show that our matching framework performs equally well to state of the art models on common variants.

Rare variant testing of imputed data: an analysis pipeline typified.

Important methodological advancements in rare variant association testing have been made recently, among them collapsing tests, kernel methods and the variable threshold (VT) technique. Typically, rare variants from a region of interest are tested for association as a group ('bin'). Rare variant studies are already routinely performed as whole-exome sequencing studies. As an alternative approach, we propose a pipeline for rare variant analysis of imputed data and develop respective quality control criteria. We provide suggestions for the choice and construction of analysis bins in whole-genome application and support the analysis with implementations of standard burden tests (COLL, CMAT) in our INTERSNP-RARE software. In addition, three rare variant regression tests (REG, FRACREG and COLLREG) are implemented. All tests are accompanied with the VT approach which optimizes the definition of 'rareness'. We integrate kernel tests as implemented in SKAT/SKAT-O into the suggested strategies. Then, we apply our analysis scheme to a genome-wide association study of Alzheimer's disease. Further, we show that our pipeline leads to valid significance testing procedures with controlled type I error rates. Strong association signals surrounding the known APOE locus demonstrate statistical power. In addition, we highlight several suggestive rare variant association findings for follow-up studies, including genomic regions overlapping MCPH1, MED18 and NOTCH3. In summary, we describe and support a straightforward and cost-efficient rare variant analysis pipeline for imputed data and demonstrate its feasibility and validity. The strategy can complement rare variant studies with next generation sequencing data.

A genome-wide association meta-analysis implicates Hedgehog and Notch signaling in Dupuytren's disease.

Dupuytren's disease (DD) is a highly heritable fibrotic disorder of the hand with incompletely understood etiology. A number of genetic loci, including Wnt signaling members, have been previously identified. Our overall aim was to identify novel genetic loci, to prioritize genes within the loci for functional studies, and to assess genetic correlation with associated disorders. We performed a meta-analysis of six DD genome-wide association studies from three European countries and extensive bioinformatic follow-up analyses. Leveraging 11,320 cases and 47,023 controls, we identified 85 genome-wide significant single nucleotide polymorphisms in 56 loci, of which 11 were novel, explaining 13.3-38.1% of disease variance. Gene prioritization implicated the Hedgehog and Notch signaling pathways. We also identified a significant genetic correlation with frozen shoulder. The pathways identified highlight the potential for new therapeutic targets and provide a basis for additional mechanistic studies for a common disorder that can severely impact hand function.

mARC1 in MASLD: Modulation of lipid accumulation in human hepatocytes and adipocytes.

BACKGROUND: Mutations in the gene MTARC1 (mitochondrial amidoxime-reducing component 1) protect carriers from metabolic dysfunction-associated steatohepatitis (MASH) and cirrhosis. MTARC1 encodes the mARC1 enzyme, which is localized to the mitochondria and has no known MASH-relevant molecular function. Our studies aimed to expand on the published human genetic mARC1 data and to observe the molecular effects of mARC1 modulation in preclinical MASH models. METHODS AND RESULTS: We identified a novel human structural variant deletion in MTARC1, which is associated with various biomarkers of liver health, including alanine aminotransferase levels. Phenome-wide Mendelian Randomization analyses additionally identified novel putatively causal associations between MTARC1 expression, and esophageal varices and cardiorespiratory traits. We observed that protective MTARC1 variants decreased protein accumulation in in vitro overexpression systems and used genetic tools to study mARC1 depletion in relevant human and mouse systems. Hepatocyte mARC1 knockdown in murine MASH models reduced body weight, liver steatosis, oxidative stress, cell death, and fibrogenesis markers. mARC1 siRNA treatment and overexpression modulated lipid accumulation and cell death consistently in primary human hepatocytes, hepatocyte cell lines, and primary human adipocytes. mARC1 depletion affected the accumulation of distinct lipid species and the expression of inflammatory and mitochondrial pathway genes/proteins in both in vitro and in vivo models. CONCLUSIONS: Depleting hepatocyte mARC1 improved metabolic dysfunction-associated steatotic liver disease-related outcomes. Given the functional role of mARC1 in human adipocyte lipid accumulation, systemic targeting of mARC1 should be considered when designing mARC1 therapies. Our data point to plasma lipid biomarkers predictive of mARC1 abundance, such as Ceramide 22:1. We propose future areas of study to describe the precise molecular function of mARC1, including lipid trafficking and subcellular location within or around the mitochondria and endoplasmic reticulum.

Integrated genome-wide pathway association analysis with INTERSNP.

OBJECTIVES: Pathway association analysis (PAA) tests for an excess of moderately significant SNPs in genes from a common pathway. METHODS: We present a Monte-Carlo simulation framework that allows to formulate the main ideas of existing PAA approaches using a self-contained rather than a competitive null hypothesis. A stand-alone implementation in INTERSNP makes time-consuming communication with standard GWAS software redundant. By additional parallelization with the OpenMP API, we achieve a reduction in running time for PAA by orders of magnitude, making a power simulation study for PAA feasible. Our approach properly accounts for linkage disequilibrium and is robust with respect to residual λ inflation. RESULTS: We demonstrate that under simple, realistic disease models, PAA can actually strongly outperform the GWAS single-marker approach. PAA methods that make use of the strength of the SNP association (GenGen, Fisher's combination test), in general, perform better than ratio-based methods (ALIGATOR, SNP ratio), whereas the relative performance of gene-based scoring (ALIGATOR, GenGen) and pathway-based scoring (SNP ratio, Fisher's combination test) depends on the architecture of the assumed disease model. Finally, we present a new PAA score that models independent signals from the same gene in a regression framework and show that it is a reasonable compromise that combines the advantages of existing ideas.

Identification of de novo variants in nonsyndromic cleft lip with/without cleft palate patients with low polygenic risk scores.

BACKGROUND: Nonsyndromic cleft lip with/without cleft palate (nsCL/P) is a congenital malformation of multifactorial etiology. Research has identified >40 genome-wide significant risk loci, which explain less than 40% of nsCL/P heritability. Studies show that some of the hidden heritability is explained by rare penetrant variants. METHODS: To identify new candidate genes, we searched for highly penetrant de novo variants (DNVs) in 50 nsCL/P patient/parent-trios with a low polygenic risk for the phenotype (discovery). We prioritized DNV-carrying candidate genes from the discovery for resequencing in independent cohorts of 1010 nsCL/P patients of diverse ethnicities and 1574 population-matched controls (replication). Segregation analyses and rare variant association in the replication cohort, in combination with additional data (genome-wide association data, expression, protein-protein-interactions), were used for final prioritization. CONCLUSION: In the discovery step, 60 DNVs were identified in 60 genes, including a variant in the established nsCL/P risk gene CDH1. Re-sequencing of 32 prioritized genes led to the identification of 373 rare, likely pathogenic variants. Finally, MDN1 and PAXIP1 were prioritized as top candidates. Our findings demonstrate that DNV detection, including polygenic risk score analysis, is a powerful tool for identifying nsCL/P candidate genes, which can also be applied to other multifactorial congenital malformations.

Quick, "imputation-free" meta-analysis with proxy-SNPs.

BACKGROUND: Meta-analysis (MA) is widely used to pool genome-wide association studies (GWASes) in order to a) increase the power to detect strong or weak genotype effects or b) as a result verification method. As a consequence of differing SNP panels among genotyping chips, imputation is the method of choice within GWAS consortia to avoid losing too many SNPs in a MA. YAMAS (Yet Another Meta Analysis Software), however, enables cross-GWAS conclusions prior to finished and polished imputation runs, which eventually are time-consuming. RESULTS: Here we present a fast method to avoid forfeiting SNPs present in only a subset of studies, without relying on imputation. This is accomplished by using reference linkage disequilibrium data from 1,000 Genomes/HapMap projects to find proxy-SNPs together with in-phase alleles for SNPs missing in at least one study. MA is conducted by combining association effect estimates of a SNP and those of its proxy-SNPs. Our algorithm is implemented in the MA software YAMAS. Association results from GWAS analysis applications can be used as input files for MA, tremendously speeding up MA compared to the conventional imputation approach. We show that our proxy algorithm is well-powered and yields valuable ad hoc results, possibly providing an incentive for follow-up studies. We propose our method as a quick screening step prior to imputation-based MA, as well as an additional main approach for studies without available reference data matching the ethnicities of study participants. As a proof of principle, we analyzed six dbGaP Type II Diabetes GWAS and found that the proxy algorithm clearly outperforms naïve MA on the p-value level: for 17 out of 23 we observe an improvement on the p-value level by a factor of more than two, and a maximum improvement by a factor of 2127. CONCLUSIONS: YAMAS is an efficient and fast meta-analysis program which offers various methods, including conventional MA as well as inserting proxy-SNPs for missing markers to avoid unnecessary power loss. MA with YAMAS can be readily conducted as YAMAS provides a generic parser for heterogeneous tabulated file formats within the GWAS field and avoids cumbersome setups. In this way, it supplements the meta-analysis process.

Selected variants of the steroid-5-alpha-reductase isoforms SRD5A1 and SRD5A2 and the sex steroid hormone receptors ESR1, ESR2 and PGR: no association with female pattern hair loss identified.

Female pattern hair loss (FPHL) is a common disorder with a complex mode of inheritance. Although understanding of its etiopathogenesis is incomplete, an interaction between genetic and hormonal factors is assumed to be important. The involvement of an androgen-dependent pathway and sex steroid hormones is the most likely hypothesis. We therefore selected a total of 21 variants from the steroid-5-alpha-reductase isoforms SRD5A1 and SRD5A2, the sex steroid hormone receptors ESR1, ESR2 (oestrogen receptor) and PGR (progesterone receptor) and genotyped these in a case-control sample of 198 patients (145 UK; 53 German patients) and 329 controls (179 UK; 150 German). None of these variants showed any significant association, either in the overall UK and German samples or in the subgroup analyses. In summary, the present results, while based on a limited selection of gene variants, do not point to the involvement of SRD5A1, SRD5A2, ESR1, ESR2 or PGR in FPHL.

The exhaustive genomic scan approach, with an application to rare-variant association analysis.

Region-based genome-wide scans are usually performed by use of a priori chosen analysis regions. Such an approach will likely miss the region comprising the strongest signal and, thus, may result in increased type II error rates and decreased power. Here, we propose a genomic exhaustive scan approach that analyzes all possible subsequences and does not rely on a prior definition of the analysis regions. As a prime instance, we present a computationally ultraefficient implementation using the rare-variant collapsing test for phenotypic association, the genomic exhaustive collapsing scan (GECS). Our implementation allows for the identification of regions comprising the strongest signals in large, genome-wide rare-variant association studies while controlling the family-wise error rate via permutation. Application of GECS to two genomic data sets revealed several novel significantly associated regions for age-related macular degeneration and for schizophrenia. Our approach also offers a high potential to improve genome-wide scans for selection, methylation, and other analyses.

Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits.

Cigarette smoking is the leading cause of preventable morbidity and mortality. Genetic variation contributes to initiation, regular smoking, nicotine dependence, and cessation. We present a Fagerström Test for Nicotine Dependence (FTND)-based genome-wide association study in 58,000 European or African ancestry smokers. We observe five genome-wide significant loci, including previously unreported loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416), and extend loci reported for other smoking traits to nicotine dependence. Using the heaviness of smoking index from UK Biobank (N = 33,791), rs2714700 is consistently associated; rs1862416 is not associated, likely reflecting nicotine dependence features not captured by the heaviness of smoking index. Both variants influence nearby gene expression (rs2714700/MAGI2-AS3 in hippocampus; rs1862416/TENM2 in lung), and expression of genes spanning nicotine dependence-associated variants is enriched in cerebellum. Nicotine dependence (SNP-based heritability = 8.6%) is genetically correlated with 18 other smoking traits (rg = 0.40-1.09) and co-morbidities. Our results highlight nicotine dependence-specific loci, emphasizing the FTND as a composite phenotype that expands genetic knowledge of smoking.

Ancient DNA study reveals HLA susceptibility locus for leprosy in medieval Europeans.

Leprosy, a chronic infectious disease caused by Mycobacterium leprae (M. leprae), was very common in Europe till the 16th century. Here, we perform an ancient DNA study on medieval skeletons from Denmark that show lesions specific for lepromatous leprosy (LL). First, we test the remains for M. leprae DNA to confirm the infection status of the individuals and to assess the bacterial diversity. We assemble 10 complete M. leprae genomes that all differ from each other. Second, we evaluate whether the human leukocyte antigen allele DRB1*15:01, a strong LL susceptibility factor in modern populations, also predisposed medieval Europeans to the disease. The comparison of genotype data from 69 M. leprae DNA-positive LL cases with those from contemporary and medieval controls reveals a statistically significant association in both instances. In addition, we observe that DRB1*15:01 co-occurs with DQB1*06:02 on a haplotype that is a strong risk factor for inflammatory diseases today.

Publisher Correction: Identification and characterization of two functional variants in the human longevity gene FOXO3.

The original version of this Article contained an error in the spelling of the author Robert Häsler, which was incorrectly given as Robert Häesler. This has now been corrected in both the PDF and HTML versions of the Article.

Identification and characterization of two functional variants in the human longevity gene FOXO3.

FOXO3 is consistently annotated as a human longevity gene. However, functional variants and underlying mechanisms for the association remain unknown. Here, we perform resequencing of the FOXO3 locus and single-nucleotide variant (SNV) genotyping in three European populations. We find two FOXO3 SNVs, rs12206094 and rs4946935, to be most significantly associated with longevity and further characterize them functionally. We experimentally validate the in silico predicted allele-dependent binding of transcription factors (CTCF, SRF) to the SNVs. Specifically, in luciferase reporter assays, the longevity alleles of both variants show considerable enhancer activities that are reversed by IGF-1 treatment. An eQTL database search reveals that the alleles are also associated with higher FOXO3 mRNA expression in various human tissues, which is in line with observations in long-lived model organisms. In summary, we present experimental evidence for a functional link between common intronic variants in FOXO3 and human longevity.

Meta-analysis identifies novel risk loci and yields systematic insights into the biology of male-pattern baldness.

Male-pattern baldness (MPB) is a common and highly heritable trait characterized by androgen-dependent, progressive hair loss from the scalp. Here, we carry out the largest GWAS meta-analysis of MPB to date, comprising 10,846 early-onset cases and 11,672 controls from eight independent cohorts. We identify 63 MPB-associated loci (P<5 × 10-8, METAL) of which 23 have not been reported previously. The 63 loci explain ∼39% of the phenotypic variance in MPB and highlight several plausible candidate genes (FGF5, IRF4, DKK2) and pathways (melatonin signalling, adipogenesis) that are likely to be implicated in the key-pathophysiological features of MPB and may represent promising targets for the development of novel therapeutic options. The data provide molecular evidence that rather than being an isolated trait, MPB shares a substantial biological basis with numerous other human phenotypes and may deserve evaluation as an early prognostic marker, for example, for prostate cancer, sudden cardiac arrest and neurodegenerative disorders.

Exome sequencing identifies potential novel candidate genes in patients with unexplained colorectal adenomatous polyposis.

In up to 30% of patients with colorectal adenomatous polyposis, no germline mutation in the known genes APC, causing familial adenomatous polyposis, MUTYH, causing MUTYH-associated polyposis, and POLE or POLD1, causing Polymerase-Proofreading-associated polyposis can be identified, although a hereditary etiology is likely. To uncover new causative genes, exome sequencing was performed using DNA from leukocytes and a total of 12 colorectal adenomas from seven unrelated patients with unexplained sporadic adenomatous polyposis. For data analysis and variant filtering, an established bioinformatics pipeline including in-house tools was applied. Variants were filtered for rare truncating point mutations and copy-number variants assuming a dominant, recessive, or tumor suppressor model of inheritance. Subsequently, targeted sequence analysis of the most promising candidate genes was performed in a validation cohort of 191 unrelated patients. All relevant variants were validated by Sanger sequencing. The analysis of exome sequencing data resulted in the identification of rare loss-of-function germline mutations in three promising candidate genes (DSC2, PIEZO1, ZSWIM7). In the validation cohort, further variants predicted to be pathogenic were identified in DSC2 and PIEZO1. According to the somatic mutation spectra, the adenomas in this patient cohort follow the classical pathways of colorectal tumorigenesis. The present study identified three candidate genes which might represent rare causes for a predisposition to colorectal adenoma formation. Especially PIEZO1 (FAM38A) and ZSWIM7 (SWS1) warrant further exploration. To evaluate the clinical relevance of these genes, investigation of larger patient cohorts and functional studies are required.