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Pleiotropy is a widespread phenomenon that may increase insight into the etiology of biological and disease traits. Since genome-wide association studies frequently provide information on a single trait only, only univariate pleiotropy detection methods are applicable, with yet unknown comparative performance. Here, we compared five such methods with respect to their ability to detect pleiotropy, including meta-analysis, ASSET, conditional false discovery rate (cFDR), cross-phenotype Bayes (CPBayes), and pleiotropic analysis under the composite null hypothesis (PLACO), by performing extended computer simulations that varied the underlying etiological model for pleiotropy for a pair of traits, including the number of causal variants, degree of traits' overlap, effect sizes as well as trait prevalence, and varying sample sizes. Our results indicate that ASSET provides the best trade-off between power and protection against false positives. We then applied ASSET to a previously published International League Against Epilepsy (ILAE) consortium data set on complex epilepsies, comprising genetic generalized epilepsy and focal epilepsy cases and corresponding controls. We identified a novel candidate locus at 17q21.32 and confirmed locus 2q24.3, previously identified to act pleiotropically on both epilepsy subtypes by a mega-analysis. Functional annotation, tissue-specific expression, and regulatory function analysis as well as Bayesian colocalization analysis corroborated this result, rendering 17q21.32 a worthwhile candidate for follow-up studies on pleiotropy in epilepsies.

PurposeLarge copy number variants (CNVs) can cause a heterogeneous spectrum of rare and severe disorders. However, most CNVs are benign and are part of natural variation in human genomes. CNV pathogenicity classification, genotype-phenotype analyses, and therapeutic target identification are challenging and time-consuming tasks that require the integration and analysis of information from multiple scattered sources by experts.MethodsWe developed a web-application combining >250,000 patient and population CNVs together with a large set of biomedical annotations and provide tools for CNV classification based on ACMG/ClinGen guidelines and gene-set enrichment analyses.ResultsHere, we introduce the CNV-ClinViewer (https://cnv-ClinViewer.broadinstitute.org), an open-source web-application for clinical evaluation and visual exploration of CNVs. The application enables real-time interactive exploration of large CNV datasets in a user-friendly designed interface.ConclusionOverall, this resource facilitates semi-automated clinical CNV interpretation and genomic loci exploration and, in combination with clinical judgment, enables clinicians and researchers to formulate novel hypotheses and guide their decision-making process. Subsequently, the CNV-ClinViewer enhances for clinical investigators patient care and for basic scientists translational genomic research.

The COVID-19 pandemic is major stressor for the general population. Little is known on the sociodemographic predictors of psychological distress during this crisis. Using the CoRonavIruSHealth Impact Survey (CRISIS), psychological distress (PD) was analyzed in a population-representative cohort of 29,986 participants across Germany comparing June 2020 with three months before the pandemic. Responses of participants demonstrated an overall stark increase of PD. PD was independently predicted by young age, female gender/motherhood, higher education and residency in West-Germany with highest risk in the two largest cities of the country. Findings are discussed in the context of stress burden and stress resilience.

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. Funding information: The present study was supported by the German Research Foundation (DFG)-Grants BE 3828/8-1, LU 1944/2-1, MA 2546/5-1, and LU1944/3-1. ACKNOWLEDGMENTS: The authors thank all patients, relatives, and control individuals for their participation. We thank the German support group for individuals with cleft lip and/or palate (Wolfgang Rosenthal Gesellschaft) for assistance with recruitment.We acknowledge the invaluable assistance of all clinical, laboratory, and bioinformatic personnel. The authors thank the Next Generation Sequencing Core Facility of the Medical Faculty of the University of Bonn for sequencing the samples that were used in this study. DbGaP datasets were accessed through dbGaP accession number phs000094.v1.p1 (Supplemental Acknowledgments). Finally, the authors thank the Genome Aggregation Database (gnomAD), and all groups that provided exome and genome variant data to this resource. A full list of gnomAD contributors is provided in the gnomAD flagship paper (Karczewski et al., 2020). Open Access funding enabled and organized by Projekt DEAL.

IntroductionFormal genetics studies show that smoking is influenced by genetic factors; exploring this on the molecular level can offer deeper insight into the etiology of smoking behaviours.MethodsSummary statistics from the GWAS and Sequencing Consortium of Alcohol and Nicotine (GSCAN) Consortium were used to calculate polygenic risk scores (PRS) in a sample of ∼2,200 smokers/never-smokers. The association of PRS for Smoking Initiation (i.e. Lifetime Smoking; SI-PRS) with smoking status, and PRS for Cigarettes per Day (CpD-PRS) and Smoking Cessation (SC-PRS) with Fagerström Test for Nicotine Dependence (FTND) score were examined, as were distinct/additive effects of parental smoking on smoking status.ResultsSI-PRS explained 6.65% of variance (Nagelkerke-R2) in smoking status (p=1.71×10−24). In smokers, CpD-PRS (R2=3.15%, p=1.82×10−8) and SC-PRS (R2=2.01%; p=7.18×10−6) were associated with FTND score. Parental smoking alone explained R2=3.06% (p=2.43×10−12) of smoking status, and 1.39% when added to the most informative SI-PRS model (total R²=8.04%).ConclusionThese results show the potential utility of molecular genetic data for research investigating smoking prevention. The fact that PRS explains more variance than family history highlights progress from formal to molecular genetics; the overlap and increased predictive value when using both suggests the importance of combining these approaches.ImplicationsThis study underlines the value of using PRS to predict smoking status/behaviour. It highlights the importance of molecular genetic methods in research investigating smoking prevention and points to the necessity of combining family history and molecular genetic data.

Clinically identified genetic variants in ion channels can be benign or cause disease by increasing or decreasing the protein function. Consequently, therapeutic decision-making is challenging without molecular testing of each variant. Our biophysical knowledge of ion channel structures and function is just emerging, and it is currently not well understood which amino acid residues cause disease when mutated.We sought to systematically identify biological properties associated with variant pathogenicity across all major voltage and ligand-gated ion channel families. We collected and curated 3,049 pathogenic variants from hundreds of neurodevelopmental and other disorders and 12,546 population variants for 30 ion channel or channel subunits for which a high-quality protein structure was available. Using a wide range of bioinformatics approaches, we computed 163 structural features and tested them for pathogenic variant enrichment. We developed a novel 3D spatial distance scoring approach that enables comparisons of pathogenic and population variant distribution across protein structures.We discovered and independently replicated that several pore residue properties and proximity to the pore axis were most significantly enriched for pathogenic variants compared to population variants. Using our novel 3D scoring approach, we showed that the strongest pathogenic variant enrichment was observed for pore-lining residues and alpha-helix residues within 5Å distance from the pore axis center and not involved in gating. Within the subset of residues located at the pore, the hydrophobicity of the pore was the feature most strongly associated with variant pathogenicity. We also found an association between the identified properties and both clinical phenotypes and fucntional in vitro assays for voltage-gated sodium channels (SCN1A, SCN2A, SCN8A) and N-methyl-D-aspartate (NMDA) receptor (GRIN1, GRIN2A, GRIN2B) encoding genes. In an independent expert-curated dataset of 1,422 neurodevelopmental disorder pathogenic patient variants, and 679 electrophysiological experiments that pore axis distance is associated with seizure age of onset and cognitive performance as well as differential gain vs. loss-of-channel function.In summary, we identified biological properties associated with ion-channel malfunction and show that these are correlated with in vitro functional read-outs and clinical phenotypes in patients with neurodevelopmental disorders. Our results suggest that clinical decision support algorithms that predict variant pathogenicity and function are feasible in the future.

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.

To analyze family-based whole-genome sequence (WGS) data for complex traits, we developed a rare variant (RV) non-parametric linkage (NPL) analysis method, which has advantages over association methods. The RV-NPL differs from the NPL in that RVs are analyzed, and allele sharing among affected relative-pairs is estimated only for minor alleles. Analyzing families can increase power because causal variants with familial aggregation usually have larger effect sizes than those underlying sporadic diseases. Differing from association analysis, for NPL only affected individuals are analyzed, which can increase power, since unaffected family members can be susceptibility variant carriers. RV-NPL is robust to population substructure and admixture, inclusion of nonpathogenic variants, as well as allelic and locus heterogeneity and can readily be applied outside of coding regions. In contrast to analyzing common variants using NPL, where loci localize to large genomic regions (e.g., >50 Mb), mapped regions are well defined for RV-NPL. Using simulation studies, we demonstrate that RV-NPL is substantially more powerful than applying traditional NPL methods to analyze RVs. The RV-NPL was applied to analyze 107 late-onset Alzheimer disease (LOAD) pedigrees of Caribbean Hispanic and European ancestry with WGS data, and statistically significant linkage (LOD ≥ 3.8) was found with RVs in PSMF1 and PTPN21 which have been shown to be involved in LOAD etiology. Additionally, nominally significant linkage was observed with RVs in ABCA7, ACE, EPHA1, and SORL1, genes that were previously reported to be associated with LOAD. RV-NPL is an ideal method to elucidate the genetic etiology of complex familial diseases.

BackgroundBurden analysis in epilepsy has shown an excess of deleterious ultra-rare variants (URVs) in few gene-sets, such as known epilepsy genes, constrained genes, ion channel or GABAA receptor genes. We set out to investigate the burden of URVs in a comprehensive range of gene-sets presumed to be implicated in epileptogenesis.MethodsWe investigated several constraint and conservation-based strategies to study whole exome sequencing data from European individuals with developmental and epileptic encephalopathies (DEE, n = 1,003), genetic generalized epilepsy (GGE, n = 3,064), and non-acquired focal epilepsy (NAFE, n = 3,522), collected by the Epi25 Collaborative, compared to 3,962 ancestry-matched controls. The burden of 12 non-synonymous URVs types in 92 gene-sets was compared between epilepsy cases (DDE, GGE, NAFE) and controls using logistic regression analysis.ResultsBurden analysis of brain-expressed genes revealed an excess of different URVs types in all three epilepsy categories which was largest for missense variants in highly constrained sites (constrained missense variants). The URVs burden was prominent in neuron-specific, synaptic and developmental genes as well as genes encoding ion channels and receptors, and it was generally higher for DEE and GGE compared to NAFE. The patterns of URVs burden in gene-sets expressed in inhibitory vs. excitatory neurons or receptors suggested a high burden in both groups in DEE but a differential involvement of inhibitory genes in GGE, while excitatory genes were predominantly affected in NAFE. Top ranking susceptibility genes from a recent genome-wide association study (GWAS) of generalized and focal epilepsies displayed a higher URVs burden in constrained coding regions in GGE and NAFE, respectively.ConclusionsUsing exome-based gene-set burden analysis, we demonstrate that missense URVs affecting mainly constrained sites are enriched in neuronal genes in both common and rare severe epilepsy syndromes. Our results indicate a differential impact of these URVs in genes expressed in inhibitory vs. excitatory neurons and receptors in generalized vs. focal epilepsies. The excess of URVs in top-ranking GWAS risk-genes suggests a convergence of rare deleterious and common risk-variants in the pathogenesis of generalized and focal epilepsies.

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.

Hearing loss (HL) is one of the most common sensory defects affecting more than 466 million individuals worldwide. It is clinically and genetically heterogeneous with over 120 genes causing non-syndromic HL identified to date. Here, we performed exome sequencing (ES) on a cohort of Iranian families with no disease-causing variants in known deafness-associated genes after screening with a targeted gene panel. We identified likely causal variants in 20 out of 71 families screened. Fifteen families segregated variants in known deafness-associated genes. Eight families segregated variants in novel candidate genes for HL: DBH, TOP3A, COX18, USP31, TCF19, SCP2, TENM1, and CARMIL1. In the three of these families, intrafamilial locus heterogeneity was observed with variants in both known and novel candidate genes. In aggregate, we were able to identify the underlying genetic cause of HL in nearly 30% of our study cohort using ES. This study corroborates the observation that high-throughput DNA sequencing in populations with high rates of consanguineous marriages represents a more appropriate strategy to elucidate the genetic etiology of heterogeneous conditions such as HL.

The prediction of appearance traits by use of solely genetic information has become an established approach and a number of statistical prediction models have already been developed for this purpose. However, given limited knowledge on appearance genetics, currently available models are incomplete and do not include all causal genetic variants as predictors. Therefore such prediction models may benefit from the inclusion of additional information that acts as a proxy for this unknown genetic background. Use of priors, possibly informed by trait category prevalence values in biogeographic ancestry groups, in a Bayesian framework may thus improve the prediction accuracy of previously predicted externally visible characteristics, but has not been investigated as of yet. In this study, we assessed the impact of using trait prevalence-informed priors on the prediction performance in Bayesian models for eye, hair and skin color as well as hair structure and freckles in comparison to the respective prior-free models. Those prior-free models were either similarly defined either very close to the already established ones by using a reduced predictive marker set. However, these differences in the number of the predictive markers should not affect significantly our main outcomes. We observed that such priors often had a strong effect on the prediction performance, but to varying degrees between different traits and also different trait categories, with some categories barely showing an effect. While we found potential for improving the prediction accuracy of many of the appearance trait categories tested by using priors, our analyses also showed that misspecification of those prior values often severely diminished the accuracy compared to the respective prior-free approach. This emphasizes the importance of accurate specification of prevalence-informed priors in Bayesian prediction modeling of appearance traits. However, the existing literature knowledge on spatial prevalence is sparse for most appearance traits, including those investigated here. Due to the limitations in appearance trait prevalence knowledge, our results render the use of trait prevalence-informed priors in DNA-based appearance trait prediction currently infeasible.

EBioMedicine 72, 103588 (2021). doi:10.1016/j.ebiom.2021.103588, Published by Elsevier, Amsterdam [u.a.]

Ecuador is a multiethnic and pluricultural country with a complex history defined by migration and admixture processes. The present study aims to increase our knowledge on the Ecuadorian Native Amerindian groups and the unique South American Y-chromosome haplogroup C3-MPB373 through the analysis of up to 23 Y-chromosome STRs (Y-STRs) and several Y-SNPs in a sample of 527 Ecuadorians from 7 distinct populations and geographic areas, including Kichwa and non-Kichwa Native Amerindians, Mestizos and Afro-Ecuadorians. Our results reveal the presence of C3-MPB373 both in the Amazonian lowland Kichwa with frequencies up to 28 % and, for the first time, in notable proportions in Kichwa populations from the Ecuadorian highlands. The substantially higher frequencies of C3-MPB373 in the Amazonian lowlands found in Kichwa and Waorani individuals suggest a founder effect in that area. Notably, estimates for the time to the most recent common ancestor (TMRCA) in the range of 7.2-9.0 kya point to an ancient origin of the haplogroup and suggest an early Holocene expansion of C3-MPB373 into South America. Finally, the pairwise genetic distances (RST) separate the Kichwa Salasaka from all the other Native Amerindian and Ecuadorian groups, indicating a so far hidden diversity among the Kichwa-speaking populations and suggesting a more southern origin of this population. In sum, our study provides a more in-depth knowledge of the male genetic structure of the multiethnic Ecuadorian population, as well as a valuable reference dataset for forensic use.

Cigarette smoking is the leading cause of preventable morbidity and mortality. Knowledge is evolving on genetics underlying initiation, regular smoking, nicotine dependence (ND), and cessation. We performed a genome-wide association study using the Fagerström Test for ND (FTND) in 58,000 smokers of European or African ancestry. Five genome-wide significant loci, including two novel loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416) were identified, and loci reported for other smoking traits were extended to ND. Using the heaviness of smoking index (HSI) in the UK Biobank (N=33,791), rs2714700 was consistently associated, but rs1862416 was not associated, likely reflecting ND features not captured by the HSI. Both variants were cis-eQTLs (rs2714700 for MAGI2-AS3 in hippocampus, rs1862416 for TENM2 in lung), and expression of genes spanning ND-associated variants was enriched in cerebellum. SNP-based heritability of ND was 8.6%, and ND was genetically correlated with 17 other smoking traits (rg=0.40–0.95) and co-morbidities. Our results emphasize the FTND as a composite phenotype that expands genetic knowledge of smoking, including loci specific to ND.

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., 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.

Complex diseases are frequently modeled as following an additive model that excludes both intra- and inter-locus interaction, while at the same time reports on non-additive biological structures are ample, prominently featuring numerous metabolic and signaling pathways. Using extensive forward population simulations, we explored the impact of three basic pathway motifs on the relationship between epidemiological parameters, including disease prevalence, relative risk, sibling recurrence risk as well as causal variant number and allele frequency. We found that some but not all pathway motifs can shift the relationships between these parameters in comparison to the classical additive liability threshold model. The strongest deviations were observed with linear, cascade-like motifs that form an integral part of many reported pathways. We also modeled maturity-onset diabetes of the young (MODY) as a combination of different basic pathway motifs and observed a good concordance in epidemiological parameter values between our simulated data under this model and those reported in the literature. Given the widespread nature of pathways, including those in the etiology of human diseases, our results re-emphasize the need for non-additive interaction modeling of genetic variants to become an additional standard approach in analyzing human genetic data.

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.

Hundreds of thousands of individuals have been genotyped in the past decades using genotyping arrays, representing both a valuable data resource for future biomedical research and a substantial investment in human genetic research. However, novel chip designs and their altered sets of single-nucleotide polymorphisms (SNPs) pose the question of how well established data resources, such as large samples of healthy controls genotyped on legacy arrays, can be combined with newer samples genotyped on those novel arrays using genotype imputation. We exemplarily investigated this question based on genotype data of 30 European and 30 African unrelated samples from the 1000 Genomes project and on markers present on two legacy SNP arrays, namely Affymetrix's Human SNP 6.0 and Illumina's 550k array, and three newer arrays, namely two Axiom arrays from Affymetrix and an OmniExpress array from Illumina. We cross-compared the imputation accuracy as well as efficacy and assessed genotype concordance among these arrays. Although the accuracy of genotype prediction was uniformly high across all arrays, the imputation efficacy, that is, the proportion of successfully imputed markers, differed considerably between array combinations in both sample sets, with legacy arrays showing a trend towards lower efficacy values compared with newer arrays when serving as imputation basis. We conclude that, given the substantial losses of markers covered by the legacy arrays, the re-genotyping of existing samples sets, in particular those of healthy population controls, would be a worthwhile endeavor to secure their continued use in the future.

China has repeatedly been the subject of genetic studies to elucidate its prehistoric and historic demography. While some studies reported a genetic distinction between Northern and Southern Han Chinese, others showed a more clinal picture of small differences within China. Here, we investigated the distribution of Y chromosome variation along administrative as well as ethnic divisions in the mainland territory of the People's Republic of China, including 28 administrative regions and 19 recognized Chinese nationalities, to assess the impact of recent demographic processes. To this end, we analyzed 37,994 Y chromosomal 17-marker haplotype profiles from the YHRD database with respect to forensic diversity measures and genetic distance between groups defined by administrative boundaries and ethnic origin. We observed high diversity throughout all Chinese provinces and ethnicities. Some ethnicities, including most prominently Kazakhs and Tibetans, showed significant genetic differentiation from the Han and other groups. However, differences between provinces were, except for those located on the Tibetan plateau, less pronounced. This discrepancy is explicable by the sizeable presence of Han speakers, who showed high genetic homogeneity all across China, in nearly all studied provinces. Furthermore, we observed a continuous genetic North-South gradient in the Han, confirming previous reports of a clinal distribution of Y chromosome variation and being in notable concordance with the previously observed spatial distribution of autosomal variation. Our findings shed light on the demographic changes in China accrued by a fast-growing and increasingly mobile population.

The study of the genetic structure of different countries within Europe has provided significant insights into their demographic history and population structure. Although France occupies a particular location at the western part of Europe and at the crossroads of migration routes, few population genetic studies have been conducted so far with genome-wide data. In this study, we analyzed SNP-chip genetic data from 2184 individuals born in France who were enrolled in two independent population cohorts. Using FineSTRUCTURE, six different genetic clusters of individuals were found that were very consistent between the two cohorts. These clusters correspond closely to geographic, historical, and linguistic divisions of France, and contain different proportions of ancestry from Stone and Bronze Age populations. By modeling the relationship between genetics and geography using EEMS, we were able to detect gene flow barriers that are similar across the two cohorts and correspond to major rivers and mountain ranges. Estimations of effective population sizes also revealed very similar patterns in both cohorts with a rapid increase of effective population sizes over the last 150 generations similar to other European countries. A marked bottleneck is also consistently seen in the two datasets starting in the 14

Whole-genome and whole-exome sequencing of individual patients allow the study of rare and potentially causative genetic variation. In this study, we sequenced DNA of a trio comprising a boy with very-early-onset inflammatory bowel disease (veoIBD) and his unaffected parents. We identified a rare, X-linked missense variant in the NAPDH oxidase NOX1 gene (c.C721T, p.R241C) in heterozygous state in the mother and in hemizygous state in the patient. We discovered that, in addition, the patient was homozygous for a common missense variant in the CYBA gene (c.T214C, p.Y72H). CYBA encodes the p22phox protein, a cofactor for NOX1. Functional assays revealed reduced cellular ROS generation and antibacterial capacity of NOX1 and p22phox variants in intestinal epithelial cells. Moreover, the identified NADPH oxidase complex variants affected NOD2-mediated immune responses, and p22phox was identified as a novel NOD2 interactor. In conclusion, we detected missense variants in a veoIBD patient that disrupt the host response to bacterial challenges and reduce protective innate immune signaling via NOD2. We assume that the patient's individual genetic makeup favored disturbed intestinal mucosal barrier function.

DNA-based prediction of externally visible characteristics has become an established approach in forensic genetics, with the aim of tracing individuals who are potentially unknown to the investigating authorities but without using this prediction as evidence in court. While a number of prediction models have been proposed, use of prior probabilities in those models has largely been absent. Here, we aim at compiling information on the spatial distribution of eye and hair coloration in order to use this as prior knowledge to improve prediction accuracy. To this end, we conducted a detailed literature review and created maps showing the eye and hair pigmentation prevalence both by countries with available information and by interpolation in order to obtain prior estimates for populations without available data. Furthermore, we assessed the association between these two traits in a very large data set. A strong limitation was the quite low amount of available data, especially outside Europe. We hope that our results will facilitate the improvement of already existing and of novel prediction methods for pigmentation traits and induce further studies on the spatial distribution of these traits.

Predicting appearance phenotypes from genotypes is relevant for various areas of human genetic research and applications such as genetic epidemiology, human history, anthropology, and particularly in forensics. Many appearance phenotypes, and thus their underlying genotypes, are highly correlated, with pigmentation traits serving as primary examples. However, all available genetic prediction models, including those for pigmentation traits currently used in forensic DNA phenotyping, ignore phenotype correlations. Here, we investigated the impact of appearance phenotype correlations on genetic appearance prediction in the exemplary case of three pigmentation traits. We used data for categorical eye, hair and skin colour as well as 41 DNA markers utilized in the recently established HIrisPlex-S system from 762 individuals with complete phenotype and genotype information. Based on these data, we performed genetic prediction modelling of eye, hair and skin colour via three different strategies, namely the established approach of predicting phenotypes solely based on genotypes while not considering phenotype correlations, and two novel approaches that considered phenotype correlations, either incorporating truly observed correlated phenotypes or DNA-predicted correlated phenotypes in addition to the DNA predictors. We found that using truly observed correlated pigmentation phenotypes as additional predictors increased the DNA-based prediction accuracies for almost all eye, hair and skin colour categories, with the largest increase for intermediate eye colour, brown hair colour, dark to black skin colour, and particularly for dark skin colour. Outcomes of dedicated computer simulations suggest that this prediction accuracy increase is due to the additional genetic information that is implicitly provided by the truly observed correlated pigmentation phenotypes used, yet not covered by the DNA predictors applied. In contrast, considering DNA-predicted correlated pigmentation phenotypes as additional predictors did not improve the performance of the genetic prediction of eye, hair and skin colour, which was in line with the results from our computer simulations. Hence, in practical applications of DNA-based appearance prediction where no phenotype knowledge is available, such as in forensic DNA phenotyping, it is not advised to use DNA-predicted correlated phenotypes as predictors in addition to the DNA predictors. In the very least, this is not recommended for the pigmentation traits and the established pigmentation DNA predictors tested here.

Objective Benign familial infantile seizures (BFIS), paroxysmal kinesigenic dyskinesia (PKD), and their combination—known as infantile convulsions and paroxysmal choreoathetosis (ICCA)—are related autosomal dominant diseases. PRRT2 (proline-rich transmembrane protein 2 gene) has been identified as the major gene in all 3 conditions, found to be mutated in 80 to 90% of familial and 30 to 35% of sporadic cases. Methods We searched for the genetic defect in PRRT2-negative, unrelated families with BFIS or ICCA using whole exome or targeted gene panel sequencing, and performed a detailed cliniconeurophysiological workup. Results In 3 families with a total of 16 affected members, we identified the same, cosegregating heterozygous missense mutation (c.4447G>A; p.E1483K) in SCN8A, encoding a voltage-gated sodium channel. A founder effect was excluded by linkage analysis. All individuals except 1 had normal cognitive and motor milestones, neuroimaging, and interictal neurological status. Fifteen affected members presented with afebrile focal or generalized tonic–clonic seizures during the first to second year of life; 5 of them experienced single unprovoked seizures later on. One patient had seizures only at school age. All patients stayed otherwise seizure-free, most without medication. Interictal electroencephalogram (EEG) was normal in all cases but 2. Five of 16 patients developed additional brief paroxysmal episodes in puberty, either dystonic/dyskinetic or “shivering” attacks, triggered by stretching, motor initiation, or emotional stimuli. In 1 case, we recorded typical PKD spells by video-EEG-polygraphy, documenting a cortical involvement. Interpretation Our study establishes SCN8A as a novel gene in which a recurrent mutation causes BFIS/ICCA, expanding the clinical–genetic spectrum of combined epileptic and dyskinetic syndromes. ANN NEUROL 2016;79:428–436

In cancer research, transcriptional aberrations are often deduced from mRNA-based gene expression profiling (GEP). Although transcriptome sequencing (RNA-seq) has gained ground in the recent past, mRNA-based microarrays remain a useful asset for high-throughput experiments in many laboratories. Possible reasons are the lower per-sample costs and the opportunity to analyze obtained GEP data in association with published data sets. There are established and widely used methods for the analysis of microarray data, which increase the comparability of different GEP data sets and facilitate data-mining approaches. However, analytic pitfalls, such as batch effects and issues of sample purity, e.g. by complex tissue composition, are often not properly addressed by these standard approaches. Moreover, most of these tools do not capitalize on the full range of public data sources or do not take advantage of the analytic possibilities for functional interpretation or of comprehensive meta-analyses. We present an overview of the most critical steps in the analysis of microarray-based GEP data. We discuss software and database query solutions that may be useful foreach step and for generally overcoming analytic challenges. Aside from machine-learning applications to classify and cluster samples, we describe clinical applications of GEP, including a novel exploratory algorithm to identify potential biomarkers of prognosis in small sample cohorts as demonstrated by exemplary data from lymphatic leukemias. Overall, this review and the attached source code provide guidance to both molecular biologists and bioinformaticians / biostatisticians to properly conduct GEP analyses as well as to evaluate the clinical / biological relevance of obtained results.

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.

BACKGROUND: Genetic generalised epilepsy is the most common type of inherited epilepsy. Despite a high concordance rate of 80% in monozygotic twins, the genetic background is still poorly understood. We aimed to investigate the burden of rare genetic variants in genetic generalised epilepsy.METHODS: For this exome-based case-control study, we used three different genetic generalised epilepsy case cohorts and three independent control cohorts, all of European descent. Cases included in the study were clinically evaluated for genetic generalised epilepsy. Whole-exome sequencing was done for the discovery case cohort, a validation case cohort, and two independent control cohorts. The replication case cohort underwent targeted next-generation sequencing of the 19 known genes encoding subunits of GABAA receptors and was compared to the respective GABAA receptor variants of a third independent control cohort. Functional investigations were done with automated two-microelectrode voltage clamping in Xenopus laevis oocytes.FINDINGS: Statistical comparison of 152 familial index cases with genetic generalised epilepsy in the discovery cohort to 549 ethnically matched controls suggested an enrichment of rare missense (Nonsyn) variants in the ensemble of 19 genes encoding GABAA receptors in cases (odds ratio [OR] 2·40 [95% CI 1·41-4·10]; pNonsyn=0·0014, adjusted pNonsyn=0·019). Enrichment for these genes was validated in a whole-exome sequencing cohort of 357 sporadic and familial genetic generalised epilepsy cases and 1485 independent controls (OR 1·46 [95% CI 1·05-2·03]; pNonsyn=0·0081, adjusted pNonsyn=0·016). Comparison of genes encoding GABAA receptors in the independent replication cohort of 583 familial and sporadic genetic generalised epilepsy index cases, based on candidate-gene panel sequencing, with a third independent control cohort of 635 controls confirmed the overall enrichment of rare missense variants for 15 GABAA receptor genes in cases compared with controls (OR 1·46 [95% CI 1·02-2·08]; pNonsyn=0·013, adjusted pNonsyn=0·027). Functional studies for two selected genes (GABRB2 and GABRA5) showed significant loss-of-function effects with reduced current amplitudes in four of seven tested variants compared with wild-type receptors.INTERPRETATION: Functionally relevant variants in genes encoding GABAA receptor subunits constitute a significant risk factor for genetic generalised epilepsy. Examination of the role of specific gene groups and pathways can disentangle the complex genetic architecture of genetic generalised epilepsy.FUNDING: EuroEPINOMICS (European Science Foundation through national funding organisations), Epicure and EpiPGX (Sixth Framework Programme and Seventh Framework Programme of the European Commission), Research Unit FOR2715 (German Research Foundation and Luxembourg National Research Fund).

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., 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.

ObjectiveHomozygous alpha1-antitrypsin (AAT) deficiency increases the risk for developing cirrhosis, whereas the relevance of heterozygous carriage remains unclear. Hence, we evaluated the impact of the two most relevant AAT variants (‘Pi*Z’ and ‘Pi*S’), present in up to 10% of Caucasians, on subjects with non-alcoholic fatty liver disease (NAFLD) or alcohol misuse.DesignWe analysed multicentric case–control cohorts consisting of 1184 people with biopsy-proven NAFLD and of 2462 people with chronic alcohol misuse, both cohorts comprising cases with cirrhosis and controls without cirrhosis. Genotyping for the Pi*Z and Pi*S variants was performed.ResultsThe Pi*Z variant presented in 13.8% of patients with cirrhotic NAFLD but only in 2.4% of counterparts without liver fibrosis (pConclusionThe Pi*Z variant is the hitherto strongest single nucleotide polymorphism-based risk factor for cirrhosis in NAFLD and alcohol misuse, whereas the Pi*S variant confers only a weak risk in alcohol misusers. As 2%–4% of Caucasians are Pi*Z carriers, this finding should be considered in genetic counselling of affected individuals.

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.

Acrocallosal syndrome (ACLS) is an autosomal recessive neurodevelopmental disorder caused by KIF7 defects and belongs to the heterogeneous group of ciliopathies related to Joubert syndrome (JBTS). While ACLS is characterized by macrocephaly, prominent forehead, depressed nasal bridge, and hypertelorism, facial dysmorphism has not been emphasized in JBTS cohorts with molecular diagnosis. To evaluate the specificity and etiology of ACLS craniofacial features, we performed whole exome or targeted Sanger sequencing in patients with the aforementioned overlapping craniofacial appearance but variable additional ciliopathy features followed by functional studies. We found (likely) pathogenic variants of KIF7 in 5 out of 9 families, including the original ACLS patients, and delineated 1000 to 4000-year-old Swiss founder alleles. Three of the remaining families had (likely) pathogenic variants in the JBTS gene C5orf42, and one patient had a novel de novo frameshift variant in SHH known to cause autosomal dominant holoprosencephaly. In accordance with the patients' craniofacial anomalies, we showed facial midline widening after silencing of C5orf42 in chicken embryos. We further supported the link between KIF7, SHH, and C5orf42 by demonstrating abnormal primary cilia and diminished response to a SHH agonist in fibroblasts of C5orf42-mutated patients, as well as axonal pathfinding errors in C5orf42-silenced chicken embryos similar to those observed after perturbation of Shh signaling. Our findings, therefore, suggest that beside the neurodevelopmental features, macrocephaly and facial widening are likely more general signs of disturbed SHH signaling. Nevertheless, long-term follow-up revealed that C5orf42-mutated patients showed catch-up development and fainting of facial features contrary to KIF7-mutated patients.

_Dear Editor_ We highly welcome the development of innovative approaches that help differentiate between monozygotic (MZ) twins based on DNA evidence in forensic casework, given that standard forensic STR profiling does not allow their individual identification. However, while Marqueta-Gracia et al. recently claimed in the Journal that almost half of the tested MZ twin pairs were discriminated based on the same three age-related CpG fragments, we present arguments and evidence demonstrating that this claim is not supported by their data. First, given the same chronological age of MZ twins per pair, applying age-related DNA methylation markers for discriminating MZ individuals within pairs appears counterintuitive. [...] Second, any data-driven claim on individual discrimination depends on the magnitude of technical error of the method used for data generation, which is especially crucial if the observed individual differences are small. [...] Third, Marqueta-Gracia et al. applied an approach to test for statistically significant inter-individual differences that appears inappropriate for the given purpose for several reasons. [...] Fourth, it appears peculiar that, although the authors have analyzed a total of six age-related CpG fragments, they based their final conclusions regarding MZ twin discrimination on only three of them (ITGA2B, ASPA, and ZIC5). [...] Fifth, cell type composition is a major challenge in epigenetic analysis. Differences in DNA methylation patterns between different cell types are well-known and typically require correction in epigenomewide association studies, an approach that should also be followed in targeted DNA methylation analysis. [...] In summary, convincing data evidence that i) age-related CpGs allow for the reliable discrimination of MZ twin individuals within pairs, ii) a small set of the same CpGs allows for reliable MZ twin discrimination across different pairs, and iii) a small set of the same CpGs allows for reliable MZ twin discrimination from forensic trace-type materials, all remain to be presented.

Objective: Increasing availability of surgically resected brain tissue from patients with focal epilepsy and Focal Cortical Dysplasia (FCD) or low-grade glio-neuronal tumors has fostered large-scale genetic examination. However, assessment of pathogenicity of germline and somatic variants remains difficult. Here, we present a state of the art evaluation of reported genes and variants associated with epileptic brain lesions. Methods: We critically re-evaluated the pathogenicity for all neuropathology-associated variants reported to date in PubMed and ClinVar databases including 101 neuropathology-associated missense variants encompassing 11 disease-related genes. We assessed gene variant tolerance and classified all identified missense variants according to guidelines from the American College of Medical Genetics and Genomics (ACMG). We further extended the bioinformatic variant prediction by introducing a novel gene-specific deleteriousness ranking for prediction scores. Results: Application of ACMG guidelines and in silico gene variant tolerance analysis classified only seven out of 11 genes to be likely disease-associated according to the reported a disease mechanism, while 61 (60.4%) of 101 variants of those genes were classified as of uncertain significance (VUS), 37 (36.6%) as being likely pathogenic (LP) and 3 (3%) as being pathogenic (P). Significance: We concluded that the majority of neuropathology-associated variants reported to date do not have enough evidence to be classified as pathogenic. Interpretation of lesion-associated variants remains challenging and application of current ACMG guidelines is recommended for interpretation and prediction.

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., 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.

Objective To test whether mutations in γ-aminobutyric acid type A receptor (GABAA-R) subunit genes contribute to the etiology of rolandic epilepsy (RE) or its atypical variants (ARE). Methods We performed exome sequencing to compare the frequency of variants in 18 GABAA-R genes in 204 European patients with RE/ARE versus 728 platform-matched controls. Identified GABRG2 variants were functionally assessed for protein stability, trafficking, postsynaptic clustering, and receptor function. Results Of 18 screened GABAA-R genes, we detected an enrichment of rare variants in the GABRG2 gene in RE/ARE patients (5 of 204, 2.45%) in comparison to controls (1 of 723, 0.14%; odds ratio = 18.07, 95% confidence interval = 2.01–855.07, p = 0.0024, pcorr = 0.043). We identified a GABRG2 splice variant (c.549-3T>G) in 2 unrelated patients as well as 3 nonsynonymous variations in this gene (p.G257R, p.R323Q, p.I389V). Functional assessment showed reduced surface expression of p.G257R and decreased GABA-evoked currents for p.R323Q. The p.G257R mutation displayed diminished levels of palmitoylation, a post-translational modification crucial for trafficking of proteins to the cell membrane. Enzymatically raised palmitoylation levels restored the surface expression of the p.G257R variant γ2 subunit. Interpretation The statistical association and the functional evidence suggest that mutations of the GABRG2 gene may increase the risk of RE/ARE. Restoring the impaired membrane trafficking of some GABRG2 mutations by enhancing palmitoylation might be an interesting therapeutic approach to reverse the pathogenic effect of such mutants. Ann Neurol 2015;77:972–986

Genetic generalised epilepsy is the most common type of inherited epilepsy. Despite a high concordance rate of 80% in monozygotic twins, the genetic background is still poorly understood. We aimed to investigate the burden of rare genetic variants in genetic generalised epilepsy.For this exome-based case-control study, we used three different genetic generalised epilepsy case cohorts and three independent control cohorts, all of European descent. Cases included in the study were clinically evaluated for genetic generalised epilepsy. Whole-exome sequencing was done for the discovery case cohort, a validation case cohort, and two independent control cohorts. The replication case cohort underwent targeted next-generation sequencing of the 19 known genes encoding subunits of GABAStatistical comparison of 152 familial index cases with genetic generalised epilepsy in the discovery cohort to 549 ethnically matched controls suggested an enrichment of rare missense (Nonsyn) variants in the ensemble of 19 genes encoding GABAFunctionally relevant variants in genes encoding GABAEuroEPINOMICS (European Science Foundation through national funding organisations), Epicure and EpiPGX (Sixth Framework Programme and Seventh Framework Programme of the European Commission), Research Unit FOR2715 (German Research Foundation and Luxembourg National Research Fund).

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. Electronic supplementary material The online version of this article (10.1186/s12920-018-0353-y) contains supplementary material, which is available to authorized users.

Individuals with Dupuytren disease (DD) are commonly seen by physicians and surgeons across multiple specialties. It is an increasingly common and disabling fibroproliferative disorder of the palmar fascia, which leads to flexion contractures of the digits, and is associated with other tissue-specific fibroses. DD affects between 5% and 25% of people of European descent and is the most common inherited disease of connective tissue. We undertook the largest GWAS to date in individuals with a surgically validated diagnosis of DD from the UK, with replication in British, Dutch, and German individuals. We validated association at all nine previously described signals and discovered 17 additional variants with p ≤ 5 × 10−8. As a proof of principle, we demonstrated correlation of the high-risk genotype at the statistically most strongly associated variant with decreased secretion of the soluble WNT-antagonist SFRP4, in surgical specimen-derived DD myofibroblasts. These results highlight important pathways involved in the pathogenesis of fibrosis, including WNT signaling, extracellular matrix modulation, and inflammation. In addition, many associated loci contain genes that were hitherto unrecognized as playing a role in fibrosis, opening up new avenues of research that may lead to novel treatments for DD and fibrosis more generally. DD represents an ideal human model disease for fibrosis research.

PurposeIncreasing availability of surgically resected brain tissue from Focal Cortical Dysplasia and low-grade epilepsy-associated tumor patients fostered large-scale genetic examination. However, assessment of germline and somatic variant pathogenicity remains difficult.MethodsHere, we critically reevaluated the pathogenicity for all neuropathology-associated variants reported to date in the PubMed and ClinVar databases, including 12 disease-related genes and 88 neuropathology-associated missense variants. We (1) assessed evolutionary gene constraint using the pLI and missense z scores, (2) applied guidelines by the American College of Medical Genetics and Genomics (ACMG), and (3) predicted pathogenicity by using PolyPhen-2, CADD, and GERP.ResultsConstraint analysis classified only seven out of 12 genes to be likely disease-associated, while 35 (40%) of those 88 variants were classified as being variants of unknown significance (VUS) and 53 (60%) as being likely pathogenic (LPII). Pathogenicity prediction yielded discrimination between neuropathology-associated variants (LPII and VUS) and rare variant scores obtained from individuals present in the Genome Aggregation Database (gnomAD).ConclusionWe conclude that several VUS are likely disease-associated and will be reclassified by future molecular evidence. In summary, interpretation of lesion-associated gene variants remains complex while the application of current ACMG guidelines including bioinformatic pathogenicity prediction will help improving interpretation and prediction.

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, 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.