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Abstract 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.

Abstract 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.

Abstract Sarcoidosis and chronic beryllium disease (CBD) are phenocopies, however the latter one has a clear trigger factor that is beryllium exposure. This study analyses single nucleotide polymorphisms (SNPs) in a large cohort for beryllium-exposed persons. SNPs were chosen for their relevance in sarcoidosis. Even though one of largest cohorts of beryllium-exposed persons was analysed, no statistically relevant association between any SNP and CBD could be verified. Notably, some SNPs exhibit inverse OR for beryllium sensitization and CBD with nominally statistical significance, which allows hypothesizing about pathophysiological role of genes for the disease triggering and development.

There is strong genetic evidence for cigarette smoking behaviors, yet little is known on nicotine dependence (ND). Here, the authors perform a genome-wide association study on ND in 58,000 smokers, identifying five genome-wide significant loci.

Background: Analyses of few gene-sets in epilepsy showed a potential to unravel key disease associations. We set out to investigate the burden of ultra-rare variants (URVs) in a comprehensive range of biologically informed gene-sets presumed to be implicated in epileptogenesis. Methods: The burden of 12 URV types in 92 gene-sets was compared between cases and controls using whole exome sequencing data from individuals of European descent with developmental and epileptic encephalopathies (DEE, n = 1,003), genetic generalized epilepsy (GGE, n = 3,064), or non-acquired focal epilepsy (NAFE, n = 3,522), collected by the Epi25 Collaborative, compared to 3,962 ancestry-matched controls. Findings: Missense URVs in highly constrained regions were enriched in neuron-specific and developmental genes, whereas genes not expressed in brain were not affected. GGE featured a higher burden in gene-sets derived from inhibitory vs. excitatory neurons or associated receptors, whereas the opposite was found for NAFE, and DEE featured a burden in both. Top-ranked susceptibility genes from recent genome-wide association studies (GWAS) and gene-sets derived from generalized vs. focal epilepsies revealed specific enrichment patterns of URVs in GGE vs. NAFE. Interpretation: Missense URVs affecting highly constrained sites differentially impact genes expressed in inhibitory vs. excitatory pathways in generalized vs. focal epilepsies. The excess of URVs in top-ranked GWAS risk-genes suggests a convergence of rare deleterious and common risk-variants in the pathogenesis of generalized and focal epilepsies. Funding: DFG Research Unit FOR-2715 (Germany), FNR (Luxembourg), NHGRI (US), NHLBI (US), DAAD (Germany).

Leprosy, caused by infection with Mycobacterium leprae, was common in Europe in the Middle Ages. Here, Krause-Kyora et al. analyze ancient DNA from a medieval Danish leprosarium to assemble 10 complete bacterial genomes and perform association analysis of the DRB1*15:01 allele with risk of leprosy infection.

Abstract Background The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require interpretation. Therefore, prediction of the effects of missense mutations using in silico tools has become a frequently used approach. Aim of this study was to assess the reliability of in silico prediction as a basis for clinical decision making in the context of hereditary breast and/or ovarian cancer. Methods We tested the performance of four prediction tools (Align-GVGD, SIFT, PolyPhen-2, MutationTaster2) using a set of 236 BRCA1/2 missense variants that had previously been classified by expert committees. However, a major pitfall in the creation of a reliable evaluation set for our purpose is the generally accepted classification of BRCA1/2 missense variants using the multifactorial likelihood model, which is partially based on Align-GVGD results. To overcome this drawback we identified 161 variants whose classification is independent of any previous in silico prediction. In addition to the performance as stand-alone tools we examined the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of combined approaches. Results PolyPhen-2 achieved the lowest sensitivity (0.67), specificity (0.67), accuracy (0.67) and MCC (0.39). Align-GVGD achieved the highest values of specificity (0.92), accuracy (0.92) and MCC (0.73), but was outperformed regarding its sensitivity (0.90) by SIFT (1.00) and MutationTaster2 (1.00). All tools suffered from poor specificities, resulting in an unacceptable proportion of false positive results in a clinical setting. This shortcoming could not be bypassed by combination of these tools. In the best case scenario, 138 families would be affected by the misclassification of neutral variants within the cohort of patients of the German Consortium for Hereditary Breast and Ovarian Cancer. Conclusion We show that due to low specificities state-of-the-art in silico prediction tools are not suitable to predict pathogenicity of variants of uncertain significance in BRCA1/2. Thus, clinical consequences should never be based solely on in silico forecasts. However, our data suggests that SIFT and MutationTaster2 could be suitable to predict benignity, as both tools did not result in false negative predictions in our analysis.

FOXO3 is one of the few established longevity genes. Here, the authors fine-map the FOXO3-longevity association to two intronic SNPs and, using luciferase assays and EMSAs, show that these SNPs affect binding of transcription factors CTCF and SRF and associate with FOXO3 expression.

Knowledge about species’ distributions is central to diverse applications in ecology, biogeography, and conservation science. Hot-spring snakes of the genus Thermophis share a distribution restricted to geothermal sites at the Tibetan Plateau (T. baileyi) and in the Hengduan Mountains (T. zhaoermii, T. shangrila). Although the suture zones of these regions are widely covered with hot springs, Thermophis populations are restricted to only a few of these habitats. Here, we use bioclimatic, topographic, and land cover data to model the potential distribution of the genus. Moreover, using logistic regression on field survey data of T. zhaoermii, we test whether hot-spring water parameters and landscape features correlate with the species’ presence or absence. Hot springs with temperatures between 45 and 100 °C and winter precipitation showed the most predictive power. At small scale, our data support the relevance of the hot-spring temperature on the species’ occurrence and indicate that also the along-valley distance from the hot-spring site to the major river might influence the distribution of Thermophis species. Our findings contribute to better understand factors shaping the current distribution of the genus and will aid in setting priorities in applied conservation biology for the hot-spring snakes.

Male-pattern baldness is a common condition in which hair is progressively lost from the scalp. Here, the authors find 23 new genetic variants associated with this condition and suggest that it is not an isolated trait but may share an underlying biological basis with various diseases.

Iran, despite its size, geographic location and past cultural influence, has largely been a blind spot for human population genetic studies. With only sparse genetic information on the Iranian population available, we pursued its genome-wide and geographic characterization based on 1021 samples from eleven ethnic groups. We show that Iranians, while close to neighboring populations, present distinct genetic variation consistent with long-standing genetic continuity, harbor high heterogeneity and different levels of consanguinity, fall apart into a cluster of similar groups and several admixed ones and have experienced numerous language adoption events in the past. Our findings render Iran an important source for human genetic variation in Western and Central Asia, will guide adequate study sampling and assist the interpretation of putative disease-implicated genetic variation. Given Iran's internal genetic heterogeneity, future studies will have to consider ethnic affiliations and possible admixture.

OBJECTIVES:Spinal muscular atrophy (SMA) is a devastating motor neuron disorder caused by homozygous loss of the survival motor neuron 1 (SMN1) gene and insufficient functional SMN protein produced by the SMN2 copy gene. Additional genetic protective modifiers such as Plastin 3 (PLS3) can counteract SMA pathology despite insufficient SMN protein. Recently, Spinraza, an SMN antisense oligonucleotide (ASO) that restores full-length SMN2 transcripts, has been FDA- and EMA-approved for SMA therapy. Hence, the availability of biomarkers allowing a reliable monitoring of disease and therapy progression would be of great importance. Our objectives were (i) to analyse the feasibility of SMN and of six SMA biomarkers identified by the BforSMA study in the Taiwanese SMA mouse model, (ii) to analyse the effect of PLS3 overexpression on these biomarkers, and (iii) to assess the impact of low-dose SMN-ASO therapy on the level of SMN and the six biomarkers. METHODS:At P10 and P21, the level of SMN and six putative biomarkers were compared among SMA, heterozygous and wild type mice, with or without PLS3 overexpression, and with or without presymptomatic low-dose SMN-ASO subcutaneous injection. SMN levels were measured in whole blood by ECL immunoassay and of six SMA putative biomarkers, namely Cartilage Oligomeric Matrix Protein (COMP), Dipeptidyl Peptidase 4 (DPP4), Tetranectin (C-type Lectin Family 3 Member B, CLEC3B), Osteopontin (Secreted Phosphoprotein 1, SPP1), Vitronectin (VTN) and Fetuin A (Alpha 2-HS Glycoprotein, AHSG) in plasma. RESULTS:SMN levels were significantly discernible between SMA, heterozygous and wild type mice. However, no significant differences were measured upon low-dose SMN-ASO treatment compared to untreated animals. Of the six biomarkers, only COMP and DPP4 showed high and SPP1 moderate correlation with the SMA phenotype. PLS3 overexpression neither influenced the SMN level nor the six biomarkers, supporting the hypothesis that PLS3 acts as an independent protective modifier.

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.

The vast majority of patients with Nijmegen Breakage Syndrome (NBS) are of Slavic origin and carry a deleterious deletion (c.657del5; rs587776650) in the NBN gene on chromosome 8q21. This mutation is essentially confined to Slavic populations and may thus be considered a Slavic founder mutation. Notably, not a single parenthood of a homozygous c.657del5 carrier has been reported to date, while heterozygous carriers do reproduce but have an increased cancer risk. These observations seem to conflict with the considerable carrier frequency of c.657del5 of 0.5% to 1% as observed in different Slavic populations because deleterious mutations would be eliminated quite rapidly by purifying selection. Therefore, we propose that heterozygous c.657del5 carriers have increased reproductive success, i.e., that the mutation confers heterozygote advantage. In fact, in our cohort study of the reproductive history of 24 NBS pedigrees from the Czech Republic, we observed that female carriers gave birth to more children on average than female non-carriers, while no such reproductive differences were observed for males. We also estimate that c.657del5 likely occurred less than 300 generations ago, thus supporting the view that the original mutation predated the historic split and subsequent spread of the 'Slavic people'. We surmise that the higher fertility of female c.657del5 carriers reflects a lower miscarriage rate in these women, thereby reflecting the role of the NBN gene product, nibrin, in the repair of DNA double strand breaks and their processing in immune gene rearrangements, telomere maintenance, and meiotic recombination, akin to the previously described role of the DNA repair genes BRCA1 and BRCA2.

Massively parallel sequencing of whole genomes and exomes has facilitated a direct assessment of causative genetic variation, now enabling the identification of genetic factors involved in rare diseases (RD) with Mendelian inheritance patterns on an almost routine basis. Here, we describe the illustrative case of a single consanguineous family where this strategy suffered from the difficulty to distinguish between two etiologically distinct disorders, namely the co-occurrence of hereditary hypophosphatemic rickets (HRR) and congenital myopathies (CM), by their phenotypic manifestation alone. We used parametric linkage analysis, homozygosity mapping and whole exome-sequencing to identify mutations underlying HRR and CM. We also present an approximate approach for assessing the probability of co-occurrence of two unlinked recessive RD in a single family as a function of the degree of consanguinity and the frequency of the disease-causing alleles. Linkage analysis and homozygosity mapping yielded elusive results when assuming a single RD, but whole-exome sequencing helped to identify two mutations in two genes, namely SLC34A3 and SEPN1, that segregated independently in this family and that have previously been linked to two etiologically different diseases. We assess the increase in chance co-occurrence of rare diseases due to consanguinity, i.e. under circumstances that generally favor linkage mapping of recessive disease, and show that this probability can increase by several orders of magnitudes. We conclude that such potential co-occurrence represents an underestimated risk when analyzing rare or undefined diseases in consanguineous families and should be given more consideration in the clinical and genetic evaluation.

Dupuytren´s disease, a fibromatosis of the connective tissue in the palm, is a common complex disease with a strong genetic component. Up to date nine genetic loci have been found to be associated with the disease. Six of these loci contain genes that code for Wnt signalling proteins. In spite of this striking first insight into the genetic factors in Dupuytren´s disease, much of the inherited risk in Dupuytren´s disease still needs to be discovered. The already identified loci jointly explain ~1% of the heritability in this disease. To further elucidate the genetic basis of Dupuytren´s disease, we performed a genome-wide meta-analysis combining three genome-wide association study (GWAS) data sets, comprising 1,580 cases and 4,480 controls. We corroborated all nine previously identified loci, six of these with genome-wide significance (p-value < 5x10-8). In addition, we identified 14 new suggestive loci (p-value < 10-5). Intriguingly, several of these new loci contain genes associated with Wnt signalling and therefore represent excellent candidates for replication. Next, we compared whole-transcriptome data between patient- and control-derived tissue samples and found the Wnt/β-catenin pathway to be the top deregulated pathway in patient samples. We then conducted network and pathway analyses in order to identify protein networks that are enriched for genes highlighted in the GWAS meta-analysis and expression data sets. We found further evidence that the Wnt signalling pathways in conjunction with other pathways may play a critical role in Dupuytren´s disease.

Guided by the practice of classical epidemiology, research into the genetic basis of complex disease has usually taken for granted the dictum that causative mutations are invariably over-represented among clinically affected as compared to unaffected individuals. However, we show that this supposition is not true and that a mutation contributing to the etiology of a complex disease can, under certain circumstances, be depleted among patients. Populations with defined disease prevalence were repeatedly simulated under a Wright-Fisher model, assuming various types of population history and genotype-phenotype relationship. For each simulation, the resulting mutation-specific population frequencies and odds ratios (ORs) were evaluated. In addition, the relationship between mutation frequency and OR was studied using real data from the NIH GWAS catalogue of reported phenotype associations of single-nucleotide polymorphisms (SNPs). While rare diseases (prevalence 1, up to 20% of mutations causing a pandemic disease (prevalence 10-20%) had ORs

The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.

Numerous studies of human populations in Europe and Asia have revealed a concordance between their extant genetic structure and the prevailing regional pattern of geography and language. For native South Americans, however, such evidence has been lacking so far. Therefore, we examined the relationship between Y-chromosomal genotype on the one hand, and male geographic origin and linguistic affiliation on the other, in the largest study of South American natives to date in terms of sampled individuals and populations. A total of 1,011 individuals, representing 50 tribal populations from 81 settlements, were genotyped for up to 17 short tandem repeat (STR) markers and 16 single nucleotide polymorphisms (Y-SNPs), the latter resolving phylogenetic lineages Q and C. Virtually no structure became apparent for the extant Y-chromosomal genetic variation of South American males that could sensibly be related to their inter-tribal geographic and linguistic relationships. This continent-wide decoupling is consistent with a rapid peopling of the continent followed by long periods of isolation in small groups. Furthermore, for the first time, we identified a distinct geographical cluster of Y-SNP lineages C-M217 (C3*) in South America. Such haplotypes are virtually absent from North and Central America, but occur at high frequency in Asia. Together with the locally confined Y-STR autocorrelation observed in our study as a whole, the available data therefore suggest a late introduction of C3* into South America no more than 6,000 years ago, perhaps via coastal or trans-Pacific routes. Extensive simulations revealed that the observed lack of haplogroup C3* among extant North and Central American natives is only compatible with low levels of migration between the ancestor populations of C3* carriers and non-carriers. In summary, our data highlight the fact that a pronounced correlation between genetic and geographic/cultural structure can only be expected under very specific conditions, most of which are likely not to have been met by the ancestors of native South Americans.

BACKGROUND:To date, liver biopsy is the only means of reliable diagnosis for fatty liver disease (FLD). Owing to the inevitable biopsy-associated health risks, however, the development of valid noninvasive diagnostic tools for FLD is well warranted. AIM:We evaluated a particular metabolic profile with regard to its ability to diagnose FLD and compared its performance to that of established phenotypes, conventional biomarkers and disease-associated genotypes. METHODS:The study population comprised 115 patients with ultrasound-diagnosed FLD and 115 sex- and age-matched controls for whom the serum concentration was measured of 138 different metabolites, including acylcarnitines, amino acids, biogenic amines, hexose, phosphatidylcholines (PCs), lyso-PCs and sphingomyelins. Established phenotypes, biomarkers, disease-associated genotypes and metabolite data were included in diagnostic models for FLD using logistic regression and partial least-squares discriminant analysis. The discriminative power of the ensuing models was compared with respect to area under curve (AUC), integrated discrimination improvement (IDI) and by way of cross-validation (CV). RESULTS:Use of metabolic markers for predicting FLD showed the best performance among all considered types of markers, yielding an AUC of 0.8993. Additional information on phenotypes, conventional biomarkers or genotypes did not significantly improve this performance. Phospholipids and branched-chain amino acids were most informative for predicting FLD. CONCLUSION:We show that the inclusion of metabolite data may substantially increase the power to diagnose FLD over that of models based solely upon phenotypes and conventional biomarkers.

BACKGROUND AND AIMS: High frequency electrosurgery has a key role in the broadening application of liver surgery. Its molecular signature, i.e. the metabolites evolving from electrocauterization which may inhibit hepatic wound healing, have not been systematically studied. METHODS: Human liver samples were thus obtained during surgery before and after electrosurgical dissection and subjected to a two-stage metabolomic screening experiment (discovery sample: N = 18, replication sample: N = 20) using gas chromatography/mass spectrometry. RESULTS: In a set of 208 chemically defined metabolites, electrosurgical dissection lead to a distinct metabolic signature resulting in a separation in the first two dimensions of a principal components analysis. Six metabolites including glycolic acid, azelaic acid, 2-n-pentylfuran, dihydroactinidiolide, 2-butenal and n-pentanal were consistently increased after electrosurgery meeting the discovery (p

Cytosine methylation provides an epigenetic level of cellular plasticity that is important for development, differentiation and cancerogenesis. We adopted microdroplet PCR to bisulfite treated target DNA in combination with second generation sequencing to simultaneously assess DNA sequence and methylation. We show measurement of methylation status in a wide range of target sequences (total 34 kb) with an average coverage of 95% (median 100%) and good correlation to the opposite strand (rho = 0.96) and to pyrosequencing (rho = 0.87). Data from lymphoma and colorectal cancer samples for SNRPN (imprinted gene), FGF6 (demethylated in the cancer samples) and HS3ST2 (methylated in the cancer samples) serve as a proof of principle showing the integration of SNP data and phased DNA-methylation information into "hepitypes" and thus the analysis of DNA methylation phylogeny in the somatic evolution of cancer.

Recent studies indicate a mutual epidemiological relationship between coronary heart disease (CHD) and periodontitis. Both diseases are associated with similar risk factors and are characterized by a chronic inflammatory process. In a candidate-gene association study, we identify an association of a genetic susceptibility locus shared by both diseases. We confirm the known association of two neighboring linkage disequilibrium regions on human chromosome 9p21.3 with CHD and show the additional strong association of these loci with the risk of aggressive periodontitis. For the lead SNP of the main associated linkage disequilibrium region, rs1333048, the odds ratio of the autosomal-recessive mode of inheritance is 1.99 (95% confidence interval 1.33-2.94; P = 6.9 x 10(-4)) for generalized aggressive periodontitis, and 1.72 (1.06-2.76; P = 2.6 x 10(-2)) for localized aggressive periodontitis. The two associated linkage disequilibrium regions map to the sequence of the large antisense noncoding RNA ANRIL, which partly overlaps regulatory and coding sequences of CDKN2A/CDKN2B. A closely located diabetes-associated variant was independent of the CHD and periodontitis risk haplotypes. Our study demonstrates that CHD and periodontitis are genetically related by at least one susceptibility locus, which is possibly involved in ANRIL activity and independent of diabetes associated risk variants within this region. Elucidation of the interplay of ANRIL transcript variants and their involvement in increased susceptibility to the interactive diseases CHD and periodontitis promises new insight into the underlying shared pathogenic mechanisms of these complex common diseases.