Genome-wide data from medieval German Jews show that the Ashkenazi founder event pre-dated the 14th century.

We report genome-wide data from 33 Ashkenazi Jews (AJ), dated to the 14th century, obtained following a salvage excavation at the medieval Jewish cemetery of Erfurt, Germany. The Erfurt individuals are genetically similar to modern AJ, but they show more variability in Eastern European-related ancestry than modern AJ. A third of the Erfurt individuals carried a mitochondrial lineage common in modern AJ and eight carried pathogenic variants known to affect AJ today. These observations, together with high levels of runs of homozygosity, suggest that the Erfurt community had already experienced the major reduction in size that affected modern AJ. The Erfurt bottleneck was more severe, implying substructure in medieval AJ. Overall, our results suggest that the AJ founder event and the acquisition of the main sources of ancestry pre-dated the 14th century and highlight late medieval genetic heterogeneity no longer present in modern AJ.

The Genomic History of the Bronze Age Southern Levant.

We report genome-wide DNA data for 73 individuals from five archaeological sites across the Bronze and Iron Ages Southern Levant. These individuals, who share the "Canaanite" material culture, can be modeled as descending from two sources: (1) earlier local Neolithic populations and (2) populations related to the Chalcolithic Zagros or the Bronze Age Caucasus. The non-local contribution increased over time, as evinced by three outliers who can be modeled as descendants of recent migrants. We show evidence that different "Canaanite" groups genetically resemble each other more than other populations. We find that Levant-related modern populations typically have substantial ancestry coming from populations related to the Chalcolithic Zagros and the Bronze Age Southern Levant. These groups also harbor ancestry from sources we cannot fully model with the available data, highlighting the critical role of post-Bronze-Age migrations into the region over the past 3,000 years.

Screening Human Embryos for Polygenic Traits Has Limited Utility.

The increasing proportion of variance in human complex traits explained by polygenic scores, along with progress in preimplantation genetic diagnosis, suggests the possibility of screening embryos for traits such as height or cognitive ability. However, the expected outcomes of embryo screening are unclear, which undermines discussion of associated ethical concerns. Here, we use theory, simulations, and real data to evaluate the potential gain of embryo screening, defined as the difference in trait value between the top-scoring embryo and the average embryo. The gain increases very slowly with the number of embryos but more rapidly with the variance explained by the score. Given current technology, the average gain due to screening would be ≈2.5 cm for height and ≈2.5 IQ points for cognitive ability. These mean values are accompanied by wide prediction intervals, and indeed, in large nuclear families, the majority of children top-scoring for height are not the tallest.

Portability of 245 polygenic scores when derived from the UK Biobank and applied to 9 ancestry groups from the same cohort.

The low portability of polygenic scores (PGSs) across global populations is a major concern that must be addressed before PGSs can be used for everyone in the clinic. Indeed, prediction accuracy has been shown to decay as a function of the genetic distance between the training and test cohorts. However, such cohorts differ not only in their genetic distance but also in their geographical distance and their data collection and assaying, conflating multiple factors. In this study, we examine the extent to which PGSs are transferable between ancestries by deriving polygenic scores for 245 curated traits from the UK Biobank data and applying them in nine ancestry groups from the same cohort. By restricting both training and testing to the UK Biobank data, we reduce the risk of environmental and genotyping confounding from using different cohorts. We define the nine ancestry groups at a sub-continental level, based on a simple, robust, and effective method that we introduce here. We then apply two different predictive methods to derive polygenic scores for all 245 phenotypes and show a systematic and dramatic reduction in portability of PGSs trained using Northwestern European individuals and applied to nine ancestry groups. These analyses demonstrate that prediction already drops off within European ancestries and reduces globally in proportion to genetic distance. Altogether, our study provides unique and robust insights into the PGS portability problem.

The landscape of autosomal-recessive pathogenic variants in European populations reveals phenotype-specific effects.

The number and distribution of recessive alleles in the population for various diseases are not known at genome-wide-scale. Based on 6,447 exome sequences of healthy, genetically unrelated Europeans of two distinct ancestries, we estimate that every individual is a carrier of at least 2 pathogenic variants in currently known autosomal-recessive (AR) genes and that 0.8%-1% of European couples are at risk of having a child affected with a severe AR genetic disorder. This risk is 16.5-fold higher for first cousins but is significantly more increased for skeletal disorders and intellectual disabilities due to their distinct genetic architecture.

Environment dominates over host genetics in shaping human gut microbiota.

Human gut microbiome composition is shaped by multiple factors but the relative contribution of host genetics remains elusive. Here we examine genotype and microbiome data from 1,046 healthy individuals with several distinct ancestral origins who share a relatively common environment, and demonstrate that the gut microbiome is not significantly associated with genetic ancestry, and that host genetics have a minor role in determining microbiome composition. We show that, by contrast, there are significant similarities in the compositions of the microbiomes of genetically unrelated individuals who share a household, and that over 20% of the inter-person microbiome variability is associated with factors related to diet, drugs and anthropometric measurements. We further demonstrate that microbiome data significantly improve the prediction accuracy for many human traits, such as glucose and obesity measures, compared to models that use only host genetic and environmental data. These results suggest that microbiome alterations aimed at improving clinical outcomes may be carried out across diverse genetic backgrounds.

Evaluation of European-based polygenic risk score for breast cancer in Ashkenazi Jewish women in Israel.

BACKGROUND: Polygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been performed in individuals of European (EUR) ancestry, and the generalisation of EUR-based PRS to other populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women. METHODS: We generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel. RESULTS: In the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28). CONCLUSIONS: Extant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.

The heritability of weight gain in infancy: A population-based twin study.

BACKGROUND: Rapid weight gain during infancy is a strong predictor of childhood obesity and is affected by genetic and environmental factors. Identifying ages with low heritability will allow for targeted interventions that might be able to prevent the adverse effects of childhood obesity. OBJECTIVES: The objective of the study is to estimate the heritability of weight gain from birth to defined ages during infancy, as well as during 6-month periods from birth to 18 months of age. We address this by leveraging large-scale computerised anthropometric data from the state-run network of well-baby clinics in Israel. METHODS: We performed a population-based twin study. We extracted weight measurements recorded between birth to 24 months from well-baby clinics for 9388 twin pairs born in Israel between 2011 and 2015. The reported sexes of the twins were used as a proxy for their zygosity status. We estimated the heritability of the weight z-score change from birth to specific ages and during particular periods in infancy. To assess the validity of the results, we repeated the analysis in a sub-cohort of twin pairs with complete weight measurements. RESULTS: During the first 2 years of life, heritability was lowest for birthweight ( h 2 = 0.40 ± 0.11 ). Heritability for weight gain since birth was highest at 4 months ( h 2 = 0.87 ± 0.13 ), and then gradually decreased until age 18 months ( h 2 = 0.62 ± 0.13 ). Estimating the heritability in 6-month intervals from birth to 18 months, heritability was highest during the 6-12-month interval ( h 2 = 0.84 ± 0.14 ), and was substantially lower during the subsequent 12-18-month interval ( h 2 = 0.43 ± 0.16 ). CONCLUSIONS: Heritability of weight gain decreases substantially in the second year of life, suggesting that this period could be an appropriate time for interventions for infants who are at an increased risk of childhood obesity.

LINADMIX: evaluating the effect of ancient admixture events on modern populations.

MOTIVATION: The rise in the number of genotyped ancient individuals provides an opportunity to estimate population admixture models for many populations. However, in models describing modern populations as mixtures of ancient ones, it is typically difficult to estimate the model mixing coefficients and to evaluate its fit to the data. RESULTS: We present LINADMIX, designed to tackle this problem by solving a constrained linear model when both the ancient and the modern genotypes are represented in a low-dimensional space. LINADMIX estimates the mixing coefficients and their standard errors, and computes a P-value for testing the model fit to the data. We quantified the performance of LINADMIX using an extensive set of simulated studies. We show that LINADMIX can accurately estimate admixture coefficients, and is robust to factors such as population size, genetic drift, proportion of missing data and various types of model misspecification. AVAILABILITY AND IMPLEMENTATION: LINADMIX is available as a python code at https://github.com/swidler/linadmix. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Limiting distribution of X-chromosomal coalescence times under first-cousin consanguineous mating.

By providing additional opportunities for coalescence within families, the presence of consanguineous unions in a population reduces coalescence times relative to non-consanguineous populations. First-cousin consanguinity can take one of six forms differing in the configuration of sexes in the pedigree of the male and female cousins who join in a consanguineous union: patrilateral parallel, patrilateral cross, matrilateral parallel, matrilateral cross, bilateral parallel, and bilateral cross. Considering populations with each of the six types of first-cousin consanguinity individually and a population with a mixture of the four unilateral types, we examine coalescent models of consanguinity. We previously computed, for first-cousin consanguinity models, the mean coalescence time for X-chromosomal loci and the limiting distribution of coalescence times for autosomal loci. Here, we use the separation-of-time-scales approach to obtain the limiting distribution of coalescence times for X-chromosomal loci. This limiting distribution has an instantaneous coalescence probability that depends on the probability that a union is consanguineous; lineages that do not coalesce instantaneously coalesce according to an exponential distribution. We study the effects on the coalescence time distribution of the type of first-cousin consanguinity, showing that patrilateral-parallel and patrilateral-cross consanguinity have no effect on X-chromosomal coalescence time distributions and that matrilateral-parallel consanguinity decreases coalescence times to a greater extent than does matrilateral-cross consanguinity.

Crossover interference and sex-specific genetic maps shape identical by descent sharing in close relatives.

Simulations of close relatives and identical by descent (IBD) segments are common in genetic studies, yet most past efforts have utilized sex averaged genetic maps and ignored crossover interference, thus omitting features known to affect the breakpoints of IBD segments. We developed Ped-sim, a method for simulating relatives that can utilize either sex-specific or sex averaged genetic maps and also either a model of crossover interference or the traditional Poisson model for inter-crossover distances. To characterize the impact of previously ignored mechanisms, we simulated data for all four combinations of these factors. We found that modeling crossover interference decreases the standard deviation of pairwise IBD proportions by 10.4% on average in full siblings through second cousins. By contrast, sex-specific maps increase this standard deviation by 4.2% on average, and also impact the number of segments relatives share. Most notably, using sex-specific maps, the number of segments half-siblings share is bimodal; and when combined with interference modeling, the probability that sixth cousins have non-zero IBD sharing ranges from 9.0 to 13.1%, depending on the sexes of the individuals through which they are related. We present new analytical results for the distributions of IBD segments under these models and show they match results from simulations. Finally, we compared IBD sharing rates between simulated and real relatives and find that the combination of sex-specific maps and interference modeling most accurately captures IBD rates in real data. Ped-sim is open source and available from https://github.com/williamslab/ped-sim.

MHC Haplotyping of SARS-CoV-2 Patients: HLA Subtypes Are Not Associated with the Presence and Severity of COVID-19 in the Israeli Population.

HLA haplotypes were found to be associated with increased risk for viral infections or disease severity in various diseases, including SARS. Several genetic variants are associated with COVID-19 severity. Studies have proposed associations, based on a very small sample and a large number of tested HLA alleles, but no clear association between HLA and COVID-19 incidence or severity has been reported. We conducted a large-scale HLA analysis of Israeli individuals who tested positive for SARS-CoV-2 infection by PCR. Overall, 72,912 individuals with known HLA haplotypes were included in the study, of whom 6413 (8.8%) were found to have SARS-CoV-2 by PCR. A total of 20,937 subjects were of Ashkenazi origin (at least 2/4 grandparents). One hundred eighty-one patients (2.8% of the infected) were hospitalized due to the disease. None of the 66 most common HLA loci (within the five HLA subgroups: A, B, C, DQB1, DRB1) was found to be associated with SARS-CoV-2 infection or hospitalization in the general Israeli population. Similarly, no association was detected in the Ashkenazi Jewish subset. Moreover, no association was found between heterozygosity in any of the HLA loci and either infection or hospitalization. We conclude that HLA haplotypes are not a major risk/protecting factor among the Israeli population for SARS-CoV-2 infection or severity. Our results suggest that if any HLA association exists with the disease it is very weak, and of limited effect on the pandemic.

Expanded clinical validation of Haploseek for comprehensive preimplantation genetic testing.

PURPOSE: We previously developed Haploseek, a method for comprehensive preimplantation genetic testing (PGT). However, some key features were missing, and the method has not yet been systematically validated. METHODS: We extended Haploseek to incorporate DNA from embryo grandparents and to allow testing of variants on chromosome X or in regions where parents share common haplotypes. We then validated Haploseek on 151 embryo biopsies from 27 clinical PGT cases. We sequenced all biopsies to low coverage (0.2×), and performed single-nucleotide polymorphism (SNP) microarray genotyping on the embryos' parents and siblings/grandparents. We used the extended Haploseek to predict chromosome copy-number variants (CNVs) and relevant variant-flanking haplotypes in each embryo. We validated haplotype predictions for each clinical sample against polymerase chain reaction (PCR)-based PGT case results, and CNV predictions against established commercial kits. RESULTS: For each of the 151 embryo biopsies, all Haploseek-derived haplotypes and CNVs were concordant with clinical PGT results. The cases included 17 autosomal dominant, 5 autosomal recessive, and 3 X-linked monogenic disorders. In addition, we evaluated 1 Robertsonian and 2 reciprocal translocations, and 17 cases of chromosome copy-number counting were performed. CONCLUSION: Our results demonstrate that Haploseek is clinically accurate and fit for all standard clinical PGT applications.

Anti-tumor necrosis factor alpha reduces the proangiogenic effects of activated macrophages derived from patients with age-related macular degeneration.

Purpose: Macrophages are believed to promote choroidal neovascularization (CNV) in neovascular age-related macular degeneration (nvAMD); however, the underlying proangiogenic mechanism is poorly understood. Therefore, we examined this mechanism in proinflammatory macrophages derived from patients with nvAMD. Methods: Monocytes were isolated from patients with nvAMD and polarized to form an M1 proangiogenic phenotype. We then screened for the role of proangiogenic cytokines expressed by these macrophages, including TNF-α, VEGF, IL-6, IL-8, and IL-1ß, using an ex vivo choroid sprouting assay and an in vivo rodent model of laser-induced CNV (LI-CNV). We also examined the value of inhibiting TNF-α inhibition with respect to reducing the proangiogenic effects of M1 macrophages. Finally, we analyzed the macrophage cytokine expression database to evaluate the feasibility of modulating the expression of TNF-α. Results: The cytokines above are expressed at high levels in patient-derived M1 macrophages. However, among the cytokines tested only TNF-α significantly increased choroid sprouting. Moreover, adoptive intravitreal transfer of M1 macrophages significantly increased LI-CNV, and blocking TNF-α abolished the proangiogenic effects of M1 macrophages in both models. An analysis of cytokine expression revealed that >50% of TNF-α expression is determined by modifiable factors. Conclusions: Blocking TNF-α can reduce the proangiogenic effects of M1 macrophages in nvAMD. Thus, activated macrophages may represent a potential therapeutic target for altering TNF-α expression in nvAMD.

Variance and limiting distribution of coalescence times in a diploid model of a consanguineous population.

Recent modeling studies interested in runs of homozygosity (ROH) and identity by descent (IBD) have sought to connect these properties of genomic sharing to pairwise coalescence times. Here, we examine a variety of features of pairwise coalescence times in models that consider consanguinity. In particular, we extend a recent diploid analysis of mean coalescence times for lineage pairs within and between individuals in a consanguineous population to derive the variance of coalescence times, studying its dependence on the frequency of consanguinity and the kinship coefficient of consanguineous relationships. We also introduce a separation-of-time-scales approach that treats consanguinity models analogously to mathematically similar phenomena such as partial selfing, using this approach to obtain coalescence-time distributions. This approach shows that the consanguinity model behaves similarly to a standard coalescent, scaling population size by a factor 1-3c, where c represents the kinship coefficient of a randomly chosen mating pair. It provides the explanation for an earlier result describing mean coalescence time in the consanguinity model in terms of c. The results extend the potential to make predictions about ROH and IBD in relation to demographic parameters of diploid populations.

FactorialHMM: fast and exact inference in factorial hidden Markov models.

MOTIVATION: Hidden Markov models (HMMs) are powerful tools for modeling processes along the genome. In a standard genomic HMM, observations are drawn, at each genomic position, from a distribution whose parameters depend on a hidden state, and the hidden states evolve along the genome as a Markov chain. Often, the hidden state is the Cartesian product of multiple processes, each evolving independently along the genome. Inference in these so-called Factorial HMMs has a naïve running time that scales as the square of the number of possible states, which by itself increases exponentially with the number of sub-chains; such a running time scaling is impractical for many applications. While faster algorithms exist, there is no available implementation suitable for developing bioinformatics applications. RESULTS: We developed FactorialHMM, a Python package for fast exact inference in Factorial HMMs. Our package allows simulating either directly from the model or from the posterior distribution of states given the observations. Additionally, we allow the inference of all key quantities related to HMMs: (i) the (Viterbi) sequence of states with the highest posterior probability; (ii) the likelihood of the data and (iii) the posterior probability (given all observations) of the marginal and pairwise state probabilities. The running time and space requirement of all procedures is linearithmic in the number of possible states. Our package is highly modular, providing the user with maximal flexibility for developing downstream applications. AVAILABILITY AND IMPLEMENTATION: https://github.com/regevs/factorial_hmm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Preconception carrier screening yield: effect of variants of unknown significance in partners of carriers with clinically significant variants.

PURPOSE: Expanded preconception carrier screening (ECS) identifies at-risk couples (ARCs) for multiple diseases. ECS reports currently include only pathogenic/likely pathogenic variants (P/LPVs). Variants of unknown significance (VUS) are not reported, unlike genomic or chromosomal array test results in other post/prenatal settings. Couples who are P/LP and VUS carriers (P/LP*VUS) may be at risk, particularly in genes with high P/LP carrier rates. We examined the possible contribution of P/LP*cVUS (coding, nonsynonymous VUS) matings to ECS yield in an Ashkenazi Jewish cohort, a population with well-established preconception screening. METHODS: We analyzed 672 Ashkenazi Jewish genome sequences (225,456 virtual matings) for variants in three different gene sets and calculated the rates of P/LP*P/LP and P/LP*cVUS matings. RESULTS: Across 180 genes, we identified 4671 variants: 144 (3.1%) P/LP and 1963 (42%) VUS. Across gene sets, the proportion of P/LP*P/LP and P/LP*cVUS ARCs was 2.7-3.8% and 6.8-7.5%, respectively. CONCLUSION: Disregarding VUS in ECS may miss ARCs. Even if only 10% of couples currently classified as P/LP*cVUS are ultimately reclassified as P/LP*P/LP, ECS yield would increase by ≈20%. While current understanding of VUS precludes VUS reporting in ECS, these findings underscore the importance of VUS reclassification. This will crucially depend on enlarging population frequency databases, especially of affected individuals.

Germline DNA replication timing shapes mammalian genome composition.

Mammalian DNA replication is a highly organized and regulated process. Large, Mb-sized regions are replicated at defined times along S-phase. Replication Timing (RT) is thought to play a role in shaping the mammalian genome by affecting mutation rates. Previous analyses relied on somatic RT profiles. However, only germline mutations are passed on to offspring and affect genomic composition. Therefore, germ cell RT information is necessary to evaluate the influences of RT on the mammalian genome. We adapted the RT mapping technique for limited amounts of cells, and measured RT from two stages in the mouse germline - primordial germ cells (PGCs) and spermatogonial stem cells (SSCs). RT in germline cells exhibited stronger correlations to both mutation rate and recombination hotspots density than those of RT in somatic tissues, emphasizing the importance of using correct tissues-of-origin for RT profiling. Germline RT maps exhibited stronger correlations to additional genetic features including GC-content, transposable elements (SINEs and LINEs), and gene density. GC content stratification and multiple regression analysis revealed independent contributions of RT to SINE, gene, mutation, and recombination hotspot densities. Together, our results establish a central role for RT in shaping multiple levels of mammalian genome composition.

The time and place of European admixture in Ashkenazi Jewish history.

The Ashkenazi Jewish (AJ) population is important in genetics due to its high rate of Mendelian disorders. AJ appeared in Europe in the 10th century, and their ancestry is thought to comprise European (EU) and Middle-Eastern (ME) components. However, both the time and place of admixture are subject to debate. Here, we attempt to characterize the AJ admixture history using a careful application of new and existing methods on a large AJ sample. Our main approach was based on local ancestry inference, in which we first classified each AJ genomic segment as EU or ME, and then compared allele frequencies along the EU segments to those of different EU populations. The contribution of each EU source was also estimated using GLOBETROTTER and haplotype sharing. The time of admixture was inferred based on multiple statistics, including ME segment lengths, the total EU ancestry per chromosome, and the correlation of ancestries along the chromosome. The major source of EU ancestry in AJ was found to be Southern Europe (≈60-80% of EU ancestry), with the rest being likely Eastern European. The inferred admixture time was ≈30 generations ago, but multiple lines of evidence suggest that it represents an average over two or more events, pre- and post-dating the founder event experienced by AJ in late medieval times. The time of the pre-bottleneck admixture event, which was likely Southern European, was estimated to ≈25-50 generations ago.