Mutations in SREBF1, Encoding Sterol Regulatory Element Binding Transcription Factor 1, Cause Autosomal-Dominant IFAP Syndrome.

IFAP syndrome is a rare genetic disorder characterized by ichthyosis follicularis, atrichia, and photophobia. Previous research found that mutations in MBTPS2, encoding site-2-protease (S2P), underlie X-linked IFAP syndrome. The present report describes the identification via whole-exome sequencing of three heterozygous mutations in SREBF1 in 11 unrelated, ethnically diverse individuals with autosomal-dominant IFAP syndrome. SREBF1 encodes sterol regulatory element-binding protein 1 (SREBP1), which promotes the transcription of lipogenes involved in the biosynthesis of fatty acids and cholesterols. This process requires cleavage of SREBP1 by site-1-protease (S1P) and S2P and subsequent translocation into the nucleus where it binds to sterol regulatory elements (SRE). The three detected SREBF1 mutations caused substitution or deletion of residues 527, 528, and 530, which are crucial for S1P cleavage. In vitro investigation of SREBP1 variants demonstrated impaired S1P cleavage, which prohibited nuclear translocation of the transcriptionally active form of SREBP1. As a result, SREBP1 variants exhibited significantly lower transcriptional activity compared to the wild-type, as demonstrated via luciferase reporter assay. RNA sequencing of the scalp skin from IFAP-affected individuals revealed a dramatic reduction in transcript levels of low-density lipoprotein receptor (LDLR) and of keratin genes known to be expressed in the outer root sheath of hair follicles. An increased rate of in situ keratinocyte apoptosis, which might contribute to skin hyperkeratosis and hypotrichosis, was also detected in scalp samples from affected individuals. Together with previous research, the present findings suggest that SREBP signaling plays an essential role in epidermal differentiation, skin barrier formation, hair growth, and eye function.

GenRisk: a tool for comprehensive genetic risk modeling.

SUMMARY: The genetic architecture of complex traits can be influenced by both many common regulatory variants with small effect sizes and rare deleterious variants in coding regions with larger effect sizes. However, the two kinds of genetic contributions are typically analyzed independently. Here, we present GenRisk, a python package for the computation and the integration of gene scores based on the burden of rare deleterious variants and common-variants-based polygenic risk scores. The derived scores can be analyzed within GenRisk to perform association tests or to derive phenotype prediction models by testing multiple classification and regression approaches. GenRisk is compatible with VCF input file formats. AVAILABILITY AND IMPLEMENTATION: GenRisk is an open source publicly available python package that can be downloaded or installed from Github (https://github.com/AldisiRana/GenRisk). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Next-generation phenotyping contributing to the identification of a 4.7 kb deletion in KANSL1 causing Koolen-de Vries syndrome.

Next-generation phenotyping (NGP) is an application of advanced methods of computer vision on medical imaging data such as portrait photos of individuals with rare disorders. NGP on portraits results in gestalt scores that can be used for the selection of appropriate genetic tests, and for the interpretation of the molecular data. Here, we report on an exceptional case of a young girl that was presented at the age of 8 and 15 and enrolled in NGP diagnostics on the latter occasion. The girl had clinical features associated with Koolen-de Vries syndrome (KdVS) and a suggestive facial gestalt. However, chromosomal microarray (CMA), Sanger sequencing, multiplex ligation-dependent probe analysis (MLPA), and trio exome sequencing remained inconclusive. Based on the highly indicative gestalt score for KdVS, the decision was made to perform genome sequencing to also evaluate noncoding variants. This analysis revealed a 4.7 kb de novo deletion partially affecting intron 6 and exon 7 of the KANSL1 gene. This is the smallest reported structural variant to date for this phenotype. The case illustrates how NGP can be integrated into the iterative diagnostic process of test selection and interpretation of sequencing results.

Bi-allelic Mutations in LSS, Encoding Lanosterol Synthase, Cause Autosomal-Recessive Hypotrichosis Simplex.

Hypotrichosis simplex (HS) is a rare form of hereditary alopecia characterized by childhood onset of diffuse and progressive scalp and body hair loss. Although research has identified a number of causal genes, genetic etiology in about 50% of HS cases remains unknown. The present report describes the identification via whole-exome sequencing of five different mutations in the gene LSS in three unrelated families with unexplained, potentially autosomal-recessive HS. Affected individuals showed sparse to absent lanugo-like scalp hair, sparse and brittle eyebrows, and sparse eyelashes and body hair. LSS encodes lanosterol synthase (LSS), which is a key enzyme in the cholesterol biosynthetic pathway. This pathway plays an important role in hair follicle biology. After localizing LSS protein expression in the hair shaft and bulb of the hair follicle, the impact of the mutations on keratinocytes was analyzed using immunoblotting and immunofluorescence. Interestingly, wild-type LSS was localized in the endoplasmic reticulum (ER), whereas mutant LSS proteins were localized in part outside of the ER. A plausible hypothesis is that this mislocalization has potential deleterious implications for hair follicle cells. Immunoblotting revealed no differences in the overall level of wild-type and mutant protein. Analyses of blood cholesterol levels revealed no decrease in cholesterol or cholesterol intermediates, thus supporting the previously proposed hypothesis of an alternative cholesterol pathway. The identification of LSS as causal gene for autosomal-recessive HS highlights the importance of the cholesterol pathway in hair follicle biology and may facilitate novel therapeutic approaches for hair loss disorders in general.

Sustained Immunoparalysis in Endotoxin-Tolerized Monocytic Cells.

Sepsis is associated with a strong inflammatory reaction triggering a complex and prolonged immune response. Septic patients have been shown to develop sustained immunosuppression due to a reduced responsiveness of leukocytes to pathogens. Changes in cellular metabolism of leukocytes have been linked to this phenomenon and contribute to the ongoing immunological derangement. However, the underlying mechanisms of these phenomena are incompletely understood. In cell culture models, we mimicked LPS tolerance conditions to provide evidence that epigenetic modifications account for monocyte metabolic changes which cause immune paralysis in restimulated septic monocytes. In detail, we observed differential methylation of CpG sites related to metabolic activity in human PBMCs 18 h after septic challenge. The examination of changes in immune function and metabolic pathways was performed in LPS-tolerized monocytic THP-1 cells. Passaged THP-1 cells, inheriting initial LPS challenge, presented with dysregulation of cytokine expression and oxygen consumption for up to 7 days after the initial LPS treatment. Proinflammatory cytokine concentrations of TNFα and IL1ß were significantly suppressed following a second LPS challenge (p < 0.001) on day 7 after first LPS stimulation. However, the analysis of cellular metabolism did not reveal any noteworthy alterations between tolerant and nontolerant THP-1 monocytes. No quantitative differences in ATP and NADH synthesis or participating enzymes of energy metabolism occurred. Our data demonstrate that the function and epigenetic modifications of septic and tolerized monocytes can be examined in vitro with the help of our LPS model. Changes in CpG site methylation and monocyte function point to a correlation between epigenetic modification in metabolic pathways and reduced monocyte function under postseptic conditions.

Mapping of cis-acting expression quantitative trait loci in human scalp hair follicles.

BACKGROUND: The association of molecular phenotypes, such as gene transcript levels, with human common genetic variation can help to improve our understanding of interindividual variability of tissue-specific gene regulation and its implications for disease. METHODS: With the aim to capture the spectrum of biological processes affected by regulatory common genetic variants (minor allele frequency ≥ 1%) in healthy hair follicles (HFs) from scalp tissue, we performed a genome-wide mapping of cis-acting expression quantitative trait loci (eQTLs) in plucked HFs, and applied these eQTLs to help further explain genomic findings for hair-related traits. RESULTS: We report 374 high-confidence eQTLs found in occipital scalp tissue, whose associated genes (eGenes) showed enrichments for metabolic, mitotic and immune processes, as well as responses to steroid hormones. We were able to replicate 68 of these associations in a smaller, independent dataset, in either frontal and/or occipital scalp tissue. Furthermore, we found three genomic regions overlapping reported genetic loci for hair shape and hair color. We found evidence to confirm the contributions of PADI3 to human variation in hair traits and suggest a novel potential candidate gene within known loci for androgenetic alopecia. CONCLUSIONS: Our study shows that an array of basic cellular functions relevant for hair growth are genetically regulated within the HF, and can be applied to aid the interpretation of interindividual variability on hair traits, as well as genetic findings for common hair disorders.

Impact on birth weight of maternal smoking throughout pregnancy mediated by DNA methylation.

BACKGROUND: Cigarette smoking has severe adverse health consequences in adults and in the offspring of mothers who smoke during pregnancy. One of the most widely reported effects of smoking during pregnancy is reduced birth weight which is in turn associated with chronic disease in adulthood. Epigenome-wide association studies have revealed that smokers show a characteristic "smoking methylation pattern", and recent authors have proposed that DNA methylation mediates the impact of maternal smoking on birth weight. The aims of the present study were to replicate previous reports that methylation mediates the effect of maternal smoking on birth weight, and for the first time to investigate whether the observed mediation effects are sex-specific in order to account for known sex-specific differences in methylation levels. METHODS: Methylation levels in the cord blood of 313 newborns were determined using the Illumina HumanMethylation450K Beadchip. A total of 5,527 CpG sites selected on the basis of evidence from the literature were tested. To determine whether the observed association between maternal smoking and birth weight was attributable to methylation, mediation analyses were performed for significant CpG sites. Separate analyses were then performed in males and females. RESULTS: Following quality control, 282 newborns eventually remained in the analysis. A total of 25 mothers had smoked consistently throughout the pregnancy. The birthweigt of newborns whose mothers had smoked throughout pregnancy was reduced by >200g. After correction for multiple testing, 30 CpGs showed differential methylation in the maternal smoking subgroup including top "smoking methylation pattern" genes AHRR, MYO1G, GFI1, CYP1A1, and CNTNAP2. The effect of maternal smoking on birth weight was partly mediated by the methylation of cg25325512 (PIM1); cg25949550 (CNTNAP2); and cg08699196 (ITGB7). Sex-specific analyses revealed a mediating effect for cg25949550 (CNTNAP2) in male newborns. CONCLUSION: The present data replicate previous findings that methylation can mediate the effect of maternal smoking on birth weight. The analysis of sex-dependent mediation effects suggests that the sex of the newborn may have an influence. Larger studies are warranted to investigate the role of both the identified differentially methylated loci and the sex of the newborn in mediating the association between maternal smoking during pregnancy and birth weight.

Next-generation phenotyping integrated in a national framework for patients with ultrarare disorders improves genetic diagnostics and yields new molecular findings.

Individuals with ultrarare disorders pose a structural challenge for healthcare systems since expert clinical knowledge is required to establish diagnoses. In TRANSLATE NAMSE, a 3-year prospective study, we evaluated a novel diagnostic concept based on multidisciplinary expertise in Germany. Here we present the systematic investigation of the phenotypic and molecular genetic data of 1,577 patients who had undergone exome sequencing and were partially analyzed with next-generation phenotyping approaches. Molecular genetic diagnoses were established in 32% of the patients totaling 370 distinct molecular genetic causes, most with prevalence below 1:50,000. During the diagnostic process, 34 novel and 23 candidate genotype-phenotype associations were identified, mainly in individuals with neurodevelopmental disorders. Sequencing data of the subcohort that consented to computer-assisted analysis of their facial images with GestaltMatcher could be prioritized more efficiently compared with approaches based solely on clinical features and molecular scores. Our study demonstrates the synergy of using next-generation sequencing and phenotyping for diagnosing ultrarare diseases in routine healthcare and discovering novel etiologies by multidisciplinary teams.

Benchmarking whole exome sequencing in the German network for personalized medicine.

INTRODUCTION: Whole Exome Sequencing (WES) has emerged as an efficient tool in clinical cancer diagnostics to broaden the scope from panel-based diagnostics to screening of all genes and enabling robust determination of complex biomarkers in a single analysis. METHODS: To assess concordance, six formalin-fixed paraffin-embedded (FFPE) tissue specimens and four commercial reference standards were analyzed by WES as matched tumor-normal DNA at 21 NGS centers in Germany, each employing local wet-lab and bioinformatics. Somatic and germline variants, copy-number alterations (CNAs), and complex biomarkers were investigated. Somatic variant calling was performed in 494 diagnostically relevant cancer genes. The raw data were collected and re-analyzed with a central bioinformatic pipeline to separate wet- and dry-lab variability. RESULTS: The mean positive percentage agreement (PPA) of somatic variant calling was 76 % while the positive predictive value (PPV) was 89 % in relation to a consensus list of variants found by at least five centers. Variant filtering was identified as the main cause for divergent variant calls. Adjusting filter criteria and re-analysis increased the PPA to 88 % for all and 97 % for the clinically relevant variants. CNA calls were concordant for 82 % of genomic regions. Homologous recombination deficiency (HRD), tumor mutational burden (TMB), and microsatellite instability (MSI) status were concordant for 94 %, 93 %, and 93 % of calls, respectively. Variability of CNAs and complex biomarkers did not decrease considerably after harmonization of the bioinformatic processing and was hence attributed mainly to wet-lab differences. CONCLUSION: Continuous optimization of bioinformatic workflows and participating in round robin tests are recommended.

High-density oligonucleotide-based resequencing assay for mutations causing syndromic and non-syndromic forms of thoracic aortic aneurysms and dissections.

Thoracic aortic aneurysm and dissection is associated with increasing mortality rate that may occur as part of a syndrome or as an isolated familial condition. Several genes have been implicated in causing TAAD, though an appropriate genetic test for their parallel testing is not yet available. Herein, we describe the novel 117-kb "MFSTAAD chip" that may help to understand the genetic basis of TAAD. A custom duplicate resequencing assay was developed to cover eight genes previously described in TAAD; FBN1, TGFBR1&2, COL3A1, MYH11, ACTA2, SLC2A10 and NOTCH1. GSEQ and SeqC software were used for data analysis. The analytical sensitivity of the assay was validated by the recognition of 182 known mutations (153 point mutations, 21 deletions, 7 insertions and 1 duplication) and a cohort of 28 patients were selected to determine the mutation yield, whereby 18 of them were previously negative for mutations in the genes FBN1 and TGFBR2. The assay had significantly higher sensitivity for point mutations (100%) and the largest deletion of 16 bp was detectable through a decline in the hybridization strength. The overall analytical sensitivity was 85%. Mutation testing of 28 unrelated TAAD patients revealed 4 known and 6 possibly pathogenic mutations with a mutation yield of 32%. The MFSTAAD chip is an alternative tool to next-generation sequencing that allows parallel analysis of several genes on a single platform. Refinements in the probe design and data analysis software will increase the analytical sensitivity of insertions and deletions making this assay even more applicable for clinical testing.

Analysis of 72,469 UK Biobank exomes links rare variants to male-pattern hair loss.

Male-pattern hair loss (MPHL) is common and highly heritable. While genome-wide association studies (GWAS) have generated insights into the contribution of common variants to MPHL etiology, the relevance of rare variants remains unclear. To determine the contribution of rare variants to MPHL etiology, we perform gene-based and single-variant analyses in exome-sequencing data from 72,469 male UK Biobank participants. While our population-level risk prediction suggests that rare variants make only a minor contribution to general MPHL risk, our rare variant collapsing tests identified a total of five significant gene associations. These findings provide additional evidence for previously implicated genes (EDA2R, WNT10A) and highlight novel risk genes at and beyond GWAS loci (HEPH, CEPT1, EIF3F). Furthermore, MPHL-associated genes are enriched for genes considered causal for monogenic trichoses. Together, our findings broaden the MPHL-associated allelic spectrum and provide insights into MPHL pathobiology and a shared basis with monogenic hair loss disorders.

Gene-based burden scores identify rare variant associations for 28 blood biomarkers.

BACKGROUND: A relevant part of the genetic architecture of complex traits is still unknown; despite the discovery of many disease-associated common variants. Polygenic risk score (PRS) models are based on the evaluation of the additive effects attributable to common variants and have been successfully implemented to assess the genetic susceptibility for many phenotypes. In contrast, burden tests are often used to identify an enrichment of rare deleterious variants in specific genes. Both kinds of genetic contributions are typically analyzed independently. Many studies suggest that complex phenotypes are influenced by both low effect common variants and high effect rare deleterious variants. The aim of this paper is to integrate the effect of both common and rare functional variants for a more comprehensive genetic risk modeling. METHODS: We developed a framework combining gene-based scores based on the enrichment of rare functionally relevant variants with genome-wide PRS based on common variants for association analysis and prediction models. We applied our framework on UK Biobank dataset with genotyping and exome data and considered 28 blood biomarkers levels as target phenotypes. For each biomarker, an association analysis was performed on full cohort using gene-based scores (GBS). The cohort was then split into 3 subsets for PRS construction and feature selection, predictive model training, and independent evaluation, respectively. Prediction models were generated including either PRS, GBS or both (combined). RESULTS: Association analyses of the cohort were able to detect significant genes that were previously known to be associated with different biomarkers. Interestingly, the analyses also revealed heterogeneous effect sizes and directionality highlighting the complexity of the blood biomarkers regulation. However, the combined models for many biomarkers show little or no improvement in prediction accuracy compared to the PRS models. CONCLUSION: This study shows that rare variants play an important role in the genetic architecture of complex multifactorial traits such as blood biomarkers. However, while rare deleterious variants play a strong role at an individual level, our results indicate that classical common variant based PRS might be more informative to predict the genetic susceptibility at the population level.

NCBench: providing an open, reproducible, transparent, adaptable, and continuous benchmark approach for DNA-sequencing-based variant calling.

We present the results of the human genomic small variant calling benchmarking initiative of the German Research Foundation (DFG) funded Next Generation Sequencing Competence Network (NGS-CN) and the German Human Genome-Phenome Archive (GHGA). In this effort, we developed NCBench, a continuous benchmarking platform for the evaluation of small genomic variant callsets in terms of recall, precision, and false positive/negative error patterns. NCBench is implemented as a continuously re-evaluated open-source repository. We show that it is possible to entirely rely on public free infrastructure (Github, Github Actions, Zenodo) in combination with established open-source tools. NCBench is agnostic of the used dataset and can evaluate an arbitrary number of given callsets, while reporting the results in a visual and interactive way. We used NCBench to evaluate over 40 callsets generated by various variant calling pipelines available in the participating groups that were run on three exome datasets from different enrichment kits and at different coverages. While all pipelines achieve high overall quality, subtle systematic differences between callers and datasets exist and are made apparent by NCBench.These insights are useful to improve existing pipelines and develop new workflows. NCBench is meant to be open for the contribution of any given callset. Most importantly, for authors, it will enable the omission of repeated re-implementation of paper-specific variant calling benchmarks for the publication of new tools or pipelines, while readers will benefit from being able to (continuously) observe the performance of tools and pipelines at the time of reading instead of at the time of writing.

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

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

Genome-wide identification of disease-causing copy number variations in 450 individuals with anorectal malformations.

Anorectal malformations (ARM) represent a spectrum of rare malformations originating from a perturbated development of the embryonic hindgut. Approximately 60% occur as a part of a defined genetic syndrome or within the spectrum of additional congenital anomalies. Rare copy number variations (CNVs) have been associated with both syndromic and non-syndromic forms. The present study represents the largest study to date to explore the contribution of CNVs to the expression of ARMs. SNP-array-based molecular karyotyping was applied in 450 individuals with ARM and 4392 healthy controls. CNVs were identified from raw intensity data using PennCNV. Overlapping CNVs between cases and controls were discarded. Remaining CNVs were filtered using a stringent filter algorithm of nine filter steps. Prioritized CNVs were confirmed using qPCR. Filtering prioritized and qPCR confirmed four microscopic chromosomal anomalies and nine submicroscopic CNVs comprising seven microdeletions (del2p13.2, del4p16.2, del7q31.33, del9p24.1, del16q12.1, del18q32, del22q11.21) and two microduplications (dup2p13.2, dup17q12) in 14 individuals (12 singletons and one affected sib-pair). Within these CNVs, based on their embryonic expression data and function, we suggest FOXK2, LPP, and SALL3 as putative candidate genes. Overall, our CNV analysis identified putative microscopic and submicroscopic chromosomal rearrangements in 3% of cases. Functional characterization and re-sequencing of suggested candidate genes is warranted.

Heterogeneity and excitability of BRAFV600E-induced tumors is determined by Akt/mTOR-signaling state and Trp53-loss.

BACKGROUND: Developmental brain tumors harboring BRAFV600E somatic mutation are diverse. Here, we describe molecular factors that determine BRAFV600E-induced tumor biology and function. METHODS: Intraventricular in utero electroporation in combination with the piggyBac transposon system was utilized to generate developmental brain neoplasms, which were comprehensively analyzed with regard to growth using near-infrared in-vivo imaging, transcript signatures by RNA sequencing, and neuronal activity by multielectrode arrays. RESULTS: BRAF  V600E expression in murine neural progenitors elicits benign neoplasms composed of enlarged dysmorphic neurons and neoplastic astroglia recapitulating ganglioglioma (GG) only in concert with active Akt/mTOR-signaling. Purely glial tumors resembling aspects of polymorphous low-grade neuroepithelial tumors of the young (PLNTYs) emerge from BRAFV600E alone. Additional somatic Trp53-loss is sufficient to generate anaplastic GGs (aGGs) with glioneuronal clonality. Functionally, only BRAFV600E/pAkt tumors intrinsically generate substantial neuronal activity and show enhanced relay to adjacent tissue conferring high epilepsy propensity. In contrast, PLNTY- and aGG models lack significant spike activity, which appears in line with the glial differentiation of the former and a dysfunctional tissue structure combined with reduced neuronal transcript signatures in the latter. CONCLUSION: mTOR-signaling and Trp53-loss critically determine the biological diversity and electrical activity of BRAFV600E-induced tumors.

Reconstruction of the origin of the first major SARS-CoV-2 outbreak in Germany.

The first major COVID-19 outbreak in Germany occurred in Heinsberg in February 2020 with 388 officially reported cases. Unexpectedly, the first outbreak happened in a small town with little to no travelers. We used phylogenetic analyses to investigate the origin and spread of the virus in this outbreak. We sequenced 90 (23%) SARS-CoV-2 genomes from the 388 reported cases including the samples from the first documented cases. Phylogenetic analyses of these sequences revealed mainly two circulating strains with 74 samples assigned to lineage B.3 and 6 samples assigned to lineage B.1. Lineage B.3 was introduced first and probably caused the initial spread. Using phylogenetic analysis tools, we were able to identify closely related strains in France and hypothesized the possible introduction from France.

GestaltMatcher facilitates rare disease matching using facial phenotype descriptors.

Many monogenic disorders cause a characteristic facial morphology. Artificial intelligence can support physicians in recognizing these patterns by associating facial phenotypes with the underlying syndrome through training on thousands of patient photographs. However, this 'supervised' approach means that diagnoses are only possible if the disorder was part of the training set. To improve recognition of ultra-rare disorders, we developed GestaltMatcher, an encoder for portraits that is based on a deep convolutional neural network. Photographs of 17,560 patients with 1,115 rare disorders were used to define a Clinical Face Phenotype Space, in which distances between cases define syndromic similarity. Here we show that patients can be matched to others with the same molecular diagnosis even when the disorder was not included in the training set. Together with mutation data, GestaltMatcher could not only accelerate the clinical diagnosis of patients with ultra-rare disorders and facial dysmorphism but also enable the delineation of new phenotypes.

Iron Deficiency Caused by Intestinal Iron Loss-Novel Candidate Genes for Severe Anemia.

The adult human body contains about 4 g of iron. About 1-2 mg of iron is absorbed every day, and in healthy individuals, the same amount is excreted. We describe a patient who presents with severe iron deficiency anemia with hemoglobin levels below 6 g/dL and ferritin levels below 30 ng/mL. Although red blood cell concentrates and intravenous iron have been substituted every month for years, body iron stores remain depleted. Diagnostics have included several esophago-gastro-duodenoscopies, colonoscopies, MRI of the liver, repetitive bone marrow biopsies, psychological analysis, application of radioactive iron to determine intact erythropoiesis, and measurement of iron excretion in urine and feces. Typically, gastrointestinal bleeding is a major cause of iron loss. Surprisingly, intestinal iron excretion in stool in the patient was repetitively increased, without gastrointestinal bleeding. Furthermore, whole exome sequencing was performed in the patient and additional family members to identify potential causative genetic variants that may cause intestinal iron loss. Under different inheritance models, several rare mutations were identified, two of which (in CISD1 and KRI1) are likely to be functionally relevant. Intestinal iron loss in the current form has not yet been described and is, with high probability, the cause of the severe iron deficiency anemia in this patient.