Founded in 1634, St. Mary's City was the first English settlement in the colony of Maryland. Despite existing written records and the ability of many present-day Americans to trace their ancestry to the historic city, substantial gaps remain in our knowledge of this early founder population. To address these gaps, we analyzed the genomes of 49 individuals from 17th-century St. Mary's City to trace their genetic ancestry, examine their enduring legacy, and demonstrate the efficacy of using an identity-by-descent (IBD) approach to link historical individuals to the present. In our analysis, we identified over 1.3 million genetic relatives of the St. Mary's individuals among research participants in the 23andMe Research Institute's database. We found high rates of genetic sharing with participants from western England and Wales, suggesting a likely place of origin for many of the colonial city's earliest inhabitants. Additionally, we observed strong genetic connections with participants from Kentucky, mirroring a recorded post-Revolutionary War migration of Maryland Catholics to that region. By further integrating genealogical information from present-day research participants who share the closest genetic connections to the St. Mary's individuals, we propose possible identities for three sequenced historical St. Mary's City residents, including Thomas Greene, the second governor of the colony of Maryland. This unique case study highlights the power of genetics to restore lost identities and reconstruct historical relationships by tracing geographic signals of ancestry. VIDEO ABSTRACT.

Few African Americans have been able to trace family lineages back to ancestors who died before the 1870 United States Census, the first in which all Black people were listed by name. We analyzed 27 individuals from Maryland’s Catoctin Furnace African American Cemetery (1774–1850), identifying 41,799 genetic relatives among consenting research participants in 23andMe, Inc.’s genetic database. One of the highest concentrations of close relatives is in Maryland, suggesting that descendants of the Catoctin individuals remain in the area. We find that many of the Catoctin individuals derived African ancestry from the Wolof or Kongo groups and European ancestry from Great Britain and Ireland. This study demonstrates the power of joint analysis of historical DNA and large datasets generated through direct-to-consumer ancestry testing.

To the Editor: Of the many goals of our study of the transatlantic slave trade, one was to identify unequal sex contributions to the gene pool in admixed populations in the Americas.1Micheletti S.J. Bryc K. Ancona Esselmann S.G. Freyman W.A. Moreno M.E. Poznik G.D. Shastri A.J. Beleza S. Mountain J.L. Agee M. et al.Genetic Consequences of the Transatlantic Slave Trade in the Americas.Am. J. Hum. Genet. 2020; 107: 265-277https://doi.org/10.1016/j.ajhg.2020.06.012Abstract Full Text Full Text PDF PubMed Scopus (64) Google Scholar Our expectation was that, given historical knowledge of the slave trade, there would be evidence of African women contributing to the gene pool at a higher rate than African men and this rate would vary by geographic region.2Eltis D. A brief overview of the Trans-Atlantic Slave Trade.in: Voyages: The Trans-Atlantic Slave Trade Database. 2007: 1700-1810Google Scholar We indeed found evidence supporting this hypothesis using three methods: investigating differences in African ancestry estimates between all autosomes and the X chromosome,3Durand E.Y. Do C.B. Mountain J.L. Macpherson J.M. Ancestry Composition: A Novel, Efficient Pipeline for Ancestry Deconvolution.(Bioinformatics). 2014; Google Scholar comparing Y and mitochondrial haplogroups in genetic males, and estimating female to male contribution ratios with a model that assumes a single admixture event.4Goldberg A. Rosenberg N.A. Beyond 2/3 and 1/3: the complex signatures of sex-biased admixture on the X chromosome.Genetics. 2015; 201: 263-279https://doi.org/10.1534/genetics.115.178509Crossref PubMed Scopus (42) Google Scholar Results from all three approaches suggested a female sex-bias that was most prominent in regions of Latin America. Specifically, certain regions of Latin America had the greatest overrepresentation of African ancestry on the X chromosome, the greatest underrepresentation of African Y (paternal) haplogroups, and the highest estimates of African women reproducing compared to African men.1Micheletti S.J. Bryc K. Ancona Esselmann S.G. Freyman W.A. Moreno M.E. Poznik G.D. Shastri A.J. Beleza S. Mountain J.L. Agee M. et al.Genetic Consequences of the Transatlantic Slave Trade in the Americas.Am. J. Hum. Genet. 2020; 107: 265-277https://doi.org/10.1016/j.ajhg.2020.06.012Abstract Full Text Full Text PDF PubMed Scopus (64) Google Scholar Together, these results prompted us to make inferences about how documented historical practices shaped the genetic landscape of people in the Americas of African descent. Pfennig and Lachance5Pfenning A. Lachance J. Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportions.Am. J. Hum. Genet. 2023; 110: 359-367Abstract Full Text Full Text PDF PubMed Scopus (1) Google Scholar highlight the significance of estimating sex-biased admixture using proper models and caution our use of a model that assumes a single admixture event. We welcome more sophisticated modeling to better represent populations’ demographic histories and agree that improvements to the existing single admixture event model, such as confidence intervals, would have benefited our study. In short, if one’s goal is to accurately quantify a range of male and female contributions to the gene pool, applying a suite of models, such as those suggested by Pfennig and Lachance,5Pfenning A. Lachance J. Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportions.Am. J. Hum. Genet. 2023; 110: 359-367Abstract Full Text Full Text PDF PubMed Scopus (1) Google Scholar to robust datasets is essential. Given this was outside the scope of our paper, we are pleased to see that our aggregated data were used to further explore estimates of sex biases and that, in many cases, these estimates remain consistent across multiple studies.4Goldberg A. Rosenberg N.A. Beyond 2/3 and 1/3: the complex signatures of sex-biased admixture on the X chromosome.Genetics. 2015; 201: 263-279https://doi.org/10.1534/genetics.115.178509Crossref PubMed Scopus (42) Google Scholar,6Bryc K. Auton A. Nelson M.R. Oksenberg J.R. Hauser S.L. Williams S. Froment A. Bodo J.-M. Wambebe C. Tishkoff S.A. Bustamante C.D. Genome-wide patterns of population structure and admixture in West Africans and African Americans.Proc. Natl. Acad. Sci. USA. 2010; 107: 786-791https://doi.org/10.1073/pnas.0909559107Crossref PubMed Scopus (347) Google Scholar Nevertheless, for our purposes, estimates from the three aforementioned analyses provided substantial evidence to infer relative differences in sex-biased contribution between geographic regions. While we agree that the accuracy of estimating sex-biased admixture is dependent on properly sampled cohorts, there is a perceived misinterpretation of some of our results which could explain some of the inconsistencies highlighted by Pfennig and Lachance.5Pfenning A. Lachance J. Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportions.Am. J. Hum. Genet. 2023; 110: 359-367Abstract Full Text Full Text PDF PubMed Scopus (1) Google Scholar For instance, they note substantial amounts of unassigned ancestry in our ancestry estimates. We would like to clarify that unassigned ancestry is minute (on average, <1%); however, in our supplementary material cited by Pfennig and Lachance,5Pfenning A. Lachance J. Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportions.Am. J. Hum. Genet. 2023; 110: 359-367Abstract Full Text Full Text PDF PubMed Scopus (1) Google Scholar we only report focal populations relevant to the transatlantic slave trade that are not expected to sum to 100%. Specifically, we do not report assignments from other ancestral populations such as those from East Asia, South Asia, Western Asia, North Africa, and Oceania. Therefore, what Pfennig and Lachance describe as unassigned ancestry is ancestry not originating from African or European populations, which may lead to a fundamental misinterpretation of the dataset. Although, as demonstrated by Pfennig and Lachance,5Pfenning A. Lachance J. Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportions.Am. J. Hum. Genet. 2023; 110: 359-367Abstract Full Text Full Text PDF PubMed Scopus (1) Google Scholar the aggregated data we provided were enough to recapitulate most of our results, but perhaps not all. While we do understand the importance of open data sharing policies, 23andMe’s consent and privacy guidelines are intended to protect research participants, which is especially important for disenfranchised populations.7Thompson H.S. Valdimarsdottir H.B. Jandorf L. Redd W. Perceived disadvantages and concerns about abuses of genetic testing for cancer risk: differences across African American, Latina and Caucasian women.Patient Educ. Counsel. 2003; 51: 217-227https://doi.org/10.1016/s0738-3991(02)00219-7Crossref PubMed Scopus (0) Google Scholar Even though our study constitutes one of the largest genetic investigations of the transatlantic slave trade, it is not without limitations. Pfennig and Lachance provide an extended in-depth investigation of sex-biased admixture in our dataset that reveals sex-biased estimates will vary with models that, in many cases, better reflect the complex demographic history of admixed populations. Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportionsPfennig et al.The American Journal of Human GeneticsFebruary 02, 2023In BriefSex-biased admixture can be inferred from ancestry-specific proportions of X chromosome and autosomes. In a paper published in the American Journal of Human Genetics, Micheletti et al.1 used this approach to quantify male and female contributions following the transatlantic slave trade. Using a large dataset from 23andMe, they concluded that African and European contributions to gene pools in the Americas were much more sex biased than previously thought. We show that the reported extreme sex-specific contributions can be attributed to unassigned genetic ancestry as well as the limitations of simple models of sex-biased admixture. Full-Text PDF Open Archive

Consistent with other investigations of African genetic diversity,1,2 our study of the transatlantic slave trade found that ancestry from ethnolinguistic groups common in Nigeria was over-represented in African Americans given the number of enslaved people reported to have been forced from the Bights of Benin and Biafra directly to the US between 1515 and 1865.3,4 In response to this finding, Jackson provided historical accounts that may have contributed to this over-representation of Nigerian ancestry in the US in addition to criticisms of genetic studies using genetic data from Africa.

Ancestry deconvolution is the task of identifying the ancestral origins of chromosomal segments of admixed individuals. It has important applications, from mapping disease genes to identifying loci potentially under natural selection. However, most existing methods are limited to a small number of ancestral populations and are unsuitable for large-scale applications. In this article, we describe Ancestry Composition, a modular pipeline for accurate and efficient ancestry deconvolution. In the first stage, a string-kernel support-vector-machines classifier assigns provisional ancestry labels to short statistically phased genomic segments. In the second stage, an autoregressive pair hidden Markov model corrects phasing errors, smooths local ancestry estimates, and computes confidence scores. Using publicly available datasets and more than 12,000 individuals from the customer database of the personal genetics company, 23andMe, Inc., we have constructed a reference panel containing more than 14,000 unrelated individuals of unadmixed ancestry. We used principal components analysis (PCA) and uniform manifold approximation and projection (UMAP) to identify genetic clusters and define 45 distinct reference populations upon which to train our method. In cross-validation experiments, Ancestry Composition achieves high precision and recall.

A Correction to this paper has been published: https://doi.org/10.1038/s41591-020-01185-6.

Background: Clinical genetic testing for inherited predisposition to venous thromboembolism (VTE) is common among patients and their families. However, there is incomplete consensus about which individuals should receive testing, and the relative risks and benefits. Methods: We assessed outcomes of receiving direct-to-consumer (DTC) results for the two most common genetic risk factors for VTE, factor V Leiden in theF5gene (FVL) and prothrombin 20210G>A in theF2gene (PT). Two thousand three hundred fifty-four customers (1244 variant-positive and 1110 variant-negative individuals) of the personal genetics company 23andMe, Inc., who had received results online forF5andF2variants, participated in an online survey-based study. Participants responded to questions about perception of VTE risk, discussion of results with healthcare providers (HCPs) and recommendations received, actions taken to control risk, emotional responses to receiving risk results, and perceived value of the information. Results: Most participants (90% of variant-positive individuals, 99% of variant-negative individuals) had not previously been tested forF5and/orF2variants. The majority of variant-positive individuals correctly perceived that they were at higher than average risk for developing VTE. These individuals reported moderate rates of discussing results with HCPs (41%); receiving prevention advice from HCPs (31%), and making behavioral changes to control risk (e.g., exercising more, 30%). A minority (36%) of variant-positive individuals worried more after receiving VTE results. Nevertheless, most participants reported that knowing their risk had been an advantage (78% variant-positive and 58% variant-negative) and were satisfied knowing their genetic probability for VTE (81% variant-positive and 67% variant-negative). Conclusion: Consumers reported moderate rates of behavioral change and perceived personal benefit from receiving DTC genetic results for VTE risk.

According to historical records of transatlantic slavery, traders forcibly deported an estimated 12.5 million people from ports along the Atlantic coastline of Africa between the 16th and 19th centuries, with global impacts reaching to the present day, more than a century and a half after slavery's abolition. Such records have fueled a broad understanding of the forced migration from Africa to the Americas yet remain underexplored in concert with genetic data. Here, we analyzed genotype array data from 50,281 research participants, which-combined with historical shipping documents-illustrate that the current genetic landscape of the Americas is largely concordant with expectations derived from documentation of slave voyages. For instance, genetic connections between people in slave trading regions of Africa and disembarkation regions of the Americas generally mirror the proportion of individuals forcibly moved between those regions. While some discordances can be explained by additional records of deportations within the Americas, other discordances yield insights into variable survival rates and timing of arrival of enslaved people from specific regions of Africa. Furthermore, the greater contribution of African women to the gene pool compared to African men varies across the Americas, consistent with literature documenting regional differences in slavery practices. This investigation of the transatlantic slave trade, which is broad in scope in terms of both datasets and analyses, establishes genetic links between individuals in the Americas and populations across Atlantic Africa, yielding a more comprehensive understanding of the African roots of peoples of the Americas.

Homozygotes for the higher penetrance hemochromatosis risk allele, HFE c.845G>A (p.Cys282Tyr, or C282Y), have been reported to be at a 2- to 3-fold increased risk for colorectal cancer (CRC). These results have been reported for small sample size studies with no information about age at diagnosis for CRC. An association with age at diagnosis might alter CRC screening recommendations. We analyzed two large European ancestry datasets to assess the association of HFE genotype with CRC risk and age at CRC diagnosis. The first dataset included 59,733 CRC or advanced adenoma cases and 72,351 controls from a CRC epidemiological study consortium. The second dataset included 13,564 self-reported CRC cases and 2,880,218 controls from the personal genetics company, 23andMe. No association of the common hereditary hemochromatosis (HH) risk genotype and CRC was found in either dataset. The odds ratios (ORs) for the association of CRC and HFE C282Y homozygosity were 1.08 (95% confidence interval [CI], 0.91-1.29; p = 0.4) and 1.01 (95% CI, 0.78-1.31, p = 0.9) in the two cohorts, respectively. Age at CRC diagnosis also did not differ by HFE C282Y/C282Y genotype in either dataset. These results indicate no increased CRC risk in individuals with HH genotypes and suggest that persons with HH risk genotypes can follow population screening recommendations for CRC.

HLA class I and KIR sequences were determined for Dogon, Fulani, and Baka populations of western Africa, Mbuti of central Africa, and Datooga, Iraqw, and Hadza of eastern Africa. Study of 162 individuals identified 134 HLA class I alleles (41 HLA-A, 60 HLA-B, and 33 HLA-C). Common to all populations are three HLA-C alleles (C1+C*07:01, C1+C*07:02, and C2+C*06:02) but no HLA-A or -B Unexpectedly, no novel HLA class I was identified in these previously unstudied and anthropologically distinctive populations. In contrast, of 227 KIR detected, 22 are present in all seven populations and 28 are novel. A high diversity of HLA A-C-B haplotypes was observed. In six populations, most haplotypes are represented just once. But in the Hadza, a majority of haplotypes occur more than once, with 2 having high frequencies and 10 having intermediate frequencies. The centromeric (cen) part of the KIR locus exhibits an even balance between cenA and cenB in all seven populations. The telomeric (tel) part has an even balance of telA to telB in East Africa, but this changes across the continent to where telB is vestigial in West Africa. All four KIR ligands (A3/11, Bw4, C1, and C2) are present in six of the populations. HLA haplotypes of the Iraqw and Hadza encode two KIR ligands, whereas the other populations have an even balance between haplotypes encoding one and two KIR ligands. Individuals in these African populations have a mean of 6.8-8.4 different interactions between KIR and HLA class I, compared with 2.9-6.5 for non-Africans.

Warrier, V., Toro, R., Won, H., Leblond, C. S., Cliquet, F., Delorme, R., De Witte, W., Bralten, J., Chakrabarti, B., Børglum, A. D., Grove, J., Poelmans, G., Hinds, D. A., Bourgeron, T. and Baron­Cohen, S. (2019) Social and non­ social autism symptoms and trait domains are genetically dissociable. Communications Biology, 2. 328. ISSN 2399­3642 doi: https://doi.org/10.1038/s42003­019­0558­4 Available at http://centaur.reading.ac.uk/86053/

BACKGROUND:Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC. METHODS:Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals). RESULTS:Positive genetic correlation was observed between MD and AD (rgMD-AD = + 0.47, P = 6.6 × 10-10). AC-quantity showed positive genetic correlation with both AD (rgAD-AC quantity = + 0.75, P = 1.8 × 10-14) and MD (rgMD-AC quantity = + 0.14, P = 2.9 × 10-7), while there was negative correlation of AC-frequency with MD (rgMD-AC frequency = -0.17, P = 1.5 × 10-10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10-6). There was no evidence for reverse causation. CONCLUSION:This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.

ABSTRACTBackgroundMendelian randomization (MR) is a method for exploring observational associations to find evidence of causality.ObjectiveTo apply MR between multiple risk factors/phenotypic traits (exposures) and Parkinson’s disease (PD) in a large, unbiased manner, and to create a public resource for research.MethodsWe used two-sample MR in which the summary statistics relating to SNPs from genome wide association studies (GWASes) of 5,839 exposures curated on MR Base were used to assess causal relationships with PD. We selected the highest quality exposure GWASes for this report (n=401). For the disease outcome, summary statistics from the largest published PD GWAS were used. For each exposure, the causal effect on PD was assessed using the inverse variance weighted (IVW) method, followed by a range of sensitivity analyses. We used a false discovery rate (FDR) corrected p-value of <0.05 from the IVW analysis to prioritize traits of interest.ResultsWe observed evidence for causal associations between twelve exposures and risk of PD. Of these, nine were causal effects related to increasing adiposity and decreasing risk of PD. The remaining top exposures that affected PD risk were tea drinking, time spent watching television and forced vital capacity, but the latter two appeared to be biased by violations of underlying MR assumptions.DiscussionWe present a new platform which offers MR analyses for a total of 5,839 GWASes versus the largest PD GWASes available (https://pdgenetics.shinyapps.io/pdgenetics/). Alongside, we report further evidence to support a causal role for adiposity on lowering the risk of PD.

Summary Meiotic nondisjunction and resulting aneuploidy can lead to severe health consequences in humans. Aneuploidy rescue can restore euploidy but may result in uniparental disomy (UPD), the inheritance of both homologs of a chromosome from one parent with no representative copy from the other. Current understanding of UPD is limited to ~3,300 cases for which UPD was associated with clinical presentation due to imprinting disorders or recessive diseases. Thus, the prevalence of UPD and its phenotypic consequences in the general population are unknown. We searched for instances of UPD in over four million consented research participants from the personal genetics company 23andMe, Inc., and 431,094 UK Biobank participants. Using computationally detected DNA segments identical-by-descent (IBD) and runs of homozygosity (ROH), we identified 675 instances of UPD across both databases. Here we present the first characterization of UPD prevalence in the general population, a machine-learning framework to detect UPD using ROH, and a novel association between autism and UPD of chromosome 22.

Altered pain sensitivity is believed to play an important role in the development of chronic pain, a common debilitating condition affecting an estimated 1 of 5 adults. Pain sensitivity varies broadly between individuals, and it is notoriously difficult to measure in large population. Although pain sensitivity is known to be moderately heritable, only a limited numbers of genetics studies have been published, with limited success at identifying the genetic architecture of pain sensitivity. In this study, we deployed a pain sensitivity questionnaire (PSQ) and an at-home version of cold pressor test (CPT) in a large genotyped cohort. We performed genome-wide association study (GWAS) analysis on the PSQ scores and CPT duration, collected for 25,321 and 6,853 participants, respectively. Despite a reasonably large sample size, we identified only one genome-wide significant locus, located in the TSSC1 gene, associated with PSQ score. Genetic correlation analysis suggested that PSQ has several traits that are correlated with chronic pain states and lifestyle factors. We found that PSQ score are positively correlated to neck and shoulder pain that lasts more than 3 months and negatively correlated to acute pain sensations like fracture. Gene-based analysis followed by pathway analysis suggested that GWAS results are enriched in genes controlling Thyroid peroxidase and Melanin production. We showed that genetic variation in MC1R gene and redhead hair pigmentation is associated with an increase of pain sensitivity measured by the PSQ scores. Introduction/Background The assessment of psychometric and experimental pain sensitivity is increasingly important and may for instance be applied to predict postoperative pain and chronification at an early stage. In general, such assessments are time consuming within clinical settings. We are seeking to identify easily accessible genetic biomarkers that can be used to alert physicians in clinical practice and start early treatment to prevent the process of chronification in pain indications. The interindividual variability in pain sensitivity and perception is however large. Several genetic root causes for differences in pain signal transduction or in the interpretation of such signals in the insula and anterior cingulate cortex have been reported. So far it is still unclear what the quantitative effects of these identified mutations have in terms of magnitude. The assessment of pain sensitivity is in general difficult since there is no objective measurement of pain available and therefore subjective with a high interindividual variability. Consequently, the requirements for minimum sample sizes are high and can reach easily reach more than 100 subjects if a statistical power of 80% and p-values of 0.05 are essential. In earlier studies, it could be shown that people with red hair need higher doses of anesthetics to reach a comparable level of anesthesia than other subgroups with a different hair color phenotype. The MC1R gene plays a pivotal role for the redhair phenotype and is highly polymorphic. In our study we have analyzed and quantified the contributions for the three major MC1R SNPs to the pain sensitivity as well as novel SNPs using GWAS by using a validated pain sensitivity questionnaire with imagined painful situations as well as an experimental pain test, namely the cold pressor test. Materials and methods

INTRODUCTION: The prevalence of celiac disease (CD) is widely variable throughout the United States (US), with a higher prevalence of disease in the Northeast. The reasons for this variability are unknown. In a prior study, we detected ethnic differences within the US, using a name-based algorithm, with prevalence in patients of Jewish ethnicity similar to the overall population, and lower in persons of East Asian ethnicity. CD etiology is dependent on human leukocyte antigen (HLA) haplotype. Typically, either HLA DQ2.5 or DQ8 is required (but not sufficient) for the development of CD, with DQ2.5 being the highest-risk haplotype. To date, no study has characterized regional or ethnic differences in the frequency of CD-compatible HLA haplotypes. Thus, we aimed to measure the frequencies of DQ2.5 and DQ8 across regions and ethnicities in the US. METHODS: We assessed the frequencies of HLA DQ2.5 (DQA1*05:DQB1*02) and DQ8 (DQA1*03:DQB1*03) in an unselected group of genotyped individuals who have used direct-to-consumer genetic testing between 2013 and 2017. Eligible participants were 23andMe customers who consented to participate in research. We assayed two SNPs to classify individuals as DQ2.5 homozygous, DQ2.5 heterozygous, DQ2.5/DQ8, DQ8 homozygous, DQ8 heterozygous, and 0 detected variants. We compared the frequency of each haplotype across four regions of the US. Additionally, we used genome-wide array data to cluster participants into 8 categories that correlate highly with self-reported race and ethnicity, and compared the frequencies of these haplotypes across these ethnic categories (Table 1). RESULTS: Of 1,290,668 individuals studied, at least one CD-compatible haplotype was present in 38.7% of individuals, and this frequency was similar across the four US regions. The frequencies of DQ2.5 homozygotes were also similar across the Northeast, Midwest, South, and West (1.25%, 1.43%, 1.38%, and 1.37%, respectively). In contrast, frequencies differ across ethnic groups: the highest DQ2.5 and DQ8 frequencies were observed in European (12.01%) and Ashkenazi Jewish (16.39%) participants, respectively. CONCLUSION: Previously reported regional variability in CD prevalence in the US may not be due to differences in HLA-based susceptibility; rather, other genetic or environmental factors likely play a role in disease pathogenesis. In addition, these differences carry great significance in view of the development of HLA haplotype-specific non-dietary therapies for CD.

We conduct a large-scale genetic association analysis of educational attainment in a sample of ~1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of ~0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11–13% of the variance in educational attainment and 7–10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research. 200 Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029, Australia 201 Institute of Molecular and Cell Biology, University of Tartu, Tartu, 51010, Estonia 202 Centre for Clinical and Cognitive Neuroscience, Institute Brain Behaviour and Mental Health, Salford Royal Hospital, Manchester, M6 8HD, UK 203 Manchester Institute Collaborative Research in Ageing, University of Manchester, Manchester, M13 9PL, UK 204 Faculty of Medicine, University of Split, Croatia, Split 21000, Croatia 205 Department of Clinical Genetics, VU Medical Centre, Amsterdam, 1081 HV, The Netherlands 206 Institute of Preventive Medicine, Bispebjerg and Frederiksberg Hospitals, The Capital Region, Frederiksberg, 2000, Denmark 207 Montpellier Business School, Montpellier, 34080, France 208 Panteia, Zoetermeer, 2715 CA, The Netherlands 209 Department of Psychiatry, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands 210 Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands 211 Department of Internal Medicine, Erasmus Medical Center, Rotterdam, 3015 GE, The Netherlands DATA AVAILABILITY AND ACCESSION CODES Summary statistics can be downloaded from www.thessgac.org/data. We provide association results for all SNPs that passed qualitycontrol filters in a GWAS meta-analysis of EduYears that excludes the research participants from 23andMe. SNP-level summary statistics from analyses based entirely or in part on 23andMe data can only be reported for up to 10,000 SNPs. We provide summary statistics for all lead SNPs identified in our GWAS analyses of Cognitive Performance, Math Ability, and Highest Math and the MTAG analyses of our four phenotypes. For the complete EduYears GWAS, which includes 23andMe, clumped results for the 3,575 SNPs with P < 10−5 are provided; this P-value threshold was chosen such that the total number of SNPs across the analyses that include data from 23andMe does not exceed 10,000. Contact information for each of the cohorts included in this paper can be found in the Supplementary Note. CODE AVAILABILITY: All software used to perform these analyses are available online. URLs: Social Science Genetic Association Consortium (SSGAC) website: http://www.thessgac.org/#!data/kuzq8. Minimac2: https://genome.sph.umich.edu/wiki/Minimac2 BEAGLE v2.1.2: http://faculty.washington.edu/browning/beagle/b3.html IMPUTE2 v2.3.1: http://mathgen.stats.ox.ac.uk/impute/impute_v2.html PBWT: https://github.com/richarddurbin/pbwt IMPUTE4: https://jmarchini.org/impute-4/ ShapeIT v2.r790: http://mathgen.stats.ox.ac.uk/genetics_software/shapeit/shapeit.html BOLT-LMM: https://data.broadinstitute.org/alkesgroup/BOLT-LMM/ SNPTEST v2.4.1: https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html REGSCAN v0.2.0: https://www.geenivaramu.ee/en/tools/regscan METAL, release 2011–03-25: http://csg.sph.umich.edu/abecasis/metal/ EasyQC v9.0: http://www.uni-regensburg.de/medizin/epidemiologie-praeventivmedizin/genetische-epidemiologie/software/ ldsc v1.0.0: https://github.com/bulik/ldsc Plink, 1.90b3p: http://zzz.bwh.harvard.edu/plink/plink2.shtml LDpred v0.9.09: https://bitbucket.org/bjarni_vilhjalmsson/ldpred Stata v14.2: https://www.stata.com/install-guide/windows/download/ DEPICT (downloaded Feb 2015): https://data.broadinstitute.org/mpg/depict/ MAGMA v1.06b: https://ctg.cncr.nl/software/magma PANTHER release 20170403: http://www.geneontology.org CAVIARBF v0.2.1: https://bitbucket.org/Wenan/caviarbf MTAG software v1.0.1: https://github.com/omeed-maghzian/mtag Lee et al. Page 5 Nat Genet. Author manuscript; available in PMC 2019 February 28. A uhor M anscript

We conducted a genome-wide association study (GWAS) to identify novel predisposition alleles associated with Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs) and JAK2 V617F clonal hematopoiesis in the general population. We recruited a web-based cohort of 726 individuals with polycythemia vera, essential thrombocythemia, and myelofibrosis and 252 637 population controls unselected for hematologic phenotypes. Using a single-nucleotide polymorphism (SNP) array platform with custom probes for the JAK2 V617F mutation (V617F), we identified 497 individuals (0.2%) among the population controls who were V617F carriers. We performed a combined GWAS of the MPN cases plus V617F carriers in the control population (n = 1223) vs the remaining controls who were noncarriers for V617F (n = 252 140). For these MPN cases plus V617F carriers, we replicated the germ line JAK2 46/1 haplotype (rs59384377: odds ratio [OR] = 2.4, P = 6.6 × 10(-89)), previously associated with V617F-positive MPN. We also identified genome-wide significant associations in the TERT gene (rs7705526: OR = 1.8, P = 1.1 × 10(-32)), in SH2B3 (rs7310615: OR = 1.4, P = 3.1 × 10(-14)), and upstream of TET2 (rs1548483: OR = 2.0, P = 2.0 × 10(-9)). These associations were confirmed in a separate replication cohort of 446 V617F carriers vs 169 021 noncarriers. In a joint analysis of the combined GWAS and replication results, we identified additional genome-wide significant predisposition alleles associated with CHEK2, ATM, PINT, and GFI1B All SNP ORs were similar for MPN patients and controls who were V617F carriers. These data indicate that the same germ line variants endow individuals with a predisposition not only to MPN, but also to JAK2 V617F clonal hematopoiesis, a more common phenomenon that may foreshadow the development of an overt neoplasm.

Aim: To assess customer comprehension of health-related personal genomic testing (PGT) results. Methods: We presented sample reports of genetic results and examined responses to comprehension questions in 1,030 PGT customers (mean age: 46.7 years; 59.9% female; 79.0% college graduates; 14.9% non-White; 4.7% of Hispanic/Latino ethnicity). Sample reports presented a genetic risk for Alzheimer's disease and type 2 diabetes, carrier screening summary results for >30 conditions, results for phenylketonuria and cystic fibrosis, and drug response results for a statin drug. Logistic regression was used to identify correlates of participant comprehension. Results: Participants exhibited high overall comprehension (mean score: 79.1% correct). The highest comprehension (range: 81.1-97.4% correct) was observed in the statin drug response and carrier screening summary results, and lower comprehension (range: 63.6-74.8% correct) on specific carrier screening results. Higher levels of numeracy, genetic knowledge, and education were significantly associated with greater comprehension. Older age (≥60 years) was associated with lower comprehension scores. Conclusions: Most customers accurately interpreted the health implications of PGT results; however, comprehension varied by demographic characteristics, numeracy and genetic knowledge, and types and format of the genetic information presented. Results suggest a need to tailor the presentation of PGT results by test type and customer characteristics.