Cryptic distant relatives are common in both isolated and cosmopolitan genetic samples

Ancestry-independent risk of venous thromboembolism in individuals with sickle cell trait vs factor V Leiden

ABSTRACT

Sickle cell trait (SCT) is a risk factor for venous thromboembolism (VTE). Prior studies investigating the association between SCT and VTE have been performed nearly exclusively in Black populations. However, race-based research can contribute to systemic racism in medicine. We leveraged data from the 23andMe research cohort (4 184 082 participants) to calculate the ancestry-independent risk of VTE associated with SCT as well as comparative risk estimates for heterozygous factor V Leiden (FVL). Odds ratios (ORs) were calculated using a meta-analysis of 3 genetic ancestry groups (European [n = 3 183 142], Latine [n = 597 539], and African [n = 202 281]) and a secondary full-cohort analysis including 2 additional groups (East Asian [n = 159 863] and South Asian [n = 41 257]). Among the full cohort, 94 323 participants (2.25%) reported a history of VTE. On meta-analysis, individuals with SCT had a 1.45-fold (confidence interval [CI], 1.32-1.60) increased risk of VTE compared with SCT noncarriers, which was similar to the full-cohort estimate. The risk of pulmonary embolism (PE) in SCT (OR, 1.95; CI, 1.72-2.20) was higher than that of isolated deep venous thrombosis (DVT; OR, 1.04; CI, 0.90-1.21). FVL carriers had 3.30-fold (CI, 3.24-3.37) increased risk of VTE compared with FVL noncarriers, with a higher risk of isolated DVT (OR, 3.59; CI, 3.51-3.68) than PE (OR, 2.72; CI, 2.64-2.81). In this large, diverse cohort, the risk of VTE was increased among individuals with SCT compared with those without, independent of race or genetic ancestry. The risk of VTE with SCT was lower than that observed in FVL; however, the pattern of VTE in SCT was PE predominant, which is the opposite to that observed in FVL.

CORRECTING MODEL MISSPECIFICATION IN RELATIONSHIP ESTIMATES

The datasets of large genotyping biobanks and direct-to-consumer genetic testing companies contain many related individuals. Until now, it has been widely accepted that the most distant relationships that can be detected are around fifteen degrees (approximately 8 th cousins) and that practical relationship estimates have a ceiling around ten degrees (approximately 5 th cousins). However, we show that these assumptions are incorrect and that they are due to a misapplication of relationship estimators. In particular, relationship estimators are applied almost exclusively to putative relatives who have been identified because they share detectable tracts of DNA identically by descent (IBD). However, no existing relationship estimator conditions on the event that two individuals share at least one detectable segment of IBD anywhere in the genome. As a result, the relationship estimates obtained using existing estimators are dramatically biased for distant relationships, inferring all sufficiently distant relationships to be around ten degrees regardless of the depth of the true relationship. Existing relationship estimators are derived under a model that assumes that each pair of related individuals shares a single common ancestor (or mating pair of ancestors). This model breaks down for relationships beyond 10 generations in the past because individuals share many thousands of cryptic common ancestors due to pedigree collapse. We first derive a corrected likelihood that conditions on the event that at least one segment is observed between a pair of putative relatives and we demonstrate that the corrected likelihood largely eliminates the bias in estimates of pairwise relationships and provides a more accurate characterization of the uncertainty in these estimates. We then reformulate the relationship inference problem to account for the fact that individuals share many common ancestors, not just one. We demonstrate that the most distant relationship that can be inferred using IBD may be 200 degrees or more, rather than ten, extending the time-to-common ancestor from approximately 300 years in the past to approximately 3,000 years in the past or more. This dramatic increase in the range of relationship estimators makes it possible to infer relationships whose common ancestors lived before historical events such as European settlement of the Americas, the Transatlantic Slave Trade, and the rise and fall of the Roman Empire.

Prioritizing privacy and presentation of supportable hypothesis testing in forensic genetic genealogy investigations

Investigative leads are not generated by traditional forensic DNA testing, if the source of the forensic evidence or a 1st degree relative of unidentified human remains is not in the DNA database. In such cases, forensic genetic genealogy (FGG) can provide valuable leads. However, FGG generated genetic data contain private and sensitive information. Therefore, it is essential to deploy approaches that minimize unnecessary disclosure of these data to mitigate potential risks to individual privacy. We recommend protective practices that need not impact effective reporting of relationship identifications. Examples include performing one-to-one comparisons of DNA profiles of third-party samples and evidence samples offline with an "air gap" to the internet and shielding the specific shared single nucleotide polymorphisms (SNP) states and locations by binning adjacent SNPs in forensic reports. Such approaches reduce risk of unwanted access to or reverse engineering of third-party individuals' genetic data and can give these donors greater confidence to support use of their DNA profiles in FGG investigation.

SIMULATING PEDIGREES ASCERTAINED ON THE BASIS OF OBSERVED IBD SHARING

In large genotyping datasets, individuals often have thousands of distant cousins with whom they share detectable segments of DNA identically by descent (IBD). The ability to simulate these distant relationships is important for developing and testing methods, carrying out power analyses, and performing population genetic analyses. Because distant relatives are unlikely to share detectable IBD segments by chance, many simulation replicates are needed to sample IBD between any given pair of distant relatives. Exponentially more samples are needed to simulate observable segments of IBD simultaneously among multiple pairs of distant relatives in a single pedigree. Using existing pedigree simulation methods that do not condition on the event that IBD is observed among certain pairs of relatives, the chances of sampling shared IBD patterns that reflect those observed in real data ascertained from large genotyping datasets are vanishingly small, even for pedigrees of modest size. Here, we show how to sample recombination breakpoints on a fixed pedigree while conditioning on the event that specified pairs of individuals share at least one observed segment of IBD. The resulting simulator makes it possible to sample genotypes and IBD segments on pedigrees that reflect those ascertained from biobank scale data.

Reconstructing parent genomes using siblings and other relatives

Reconstructing the DNA of ancestors from their descendants has the potential to empower phenotypic analyses (including association and genetic nurture studies), improve pedigree reconstruction, and shed light on the ancestral population and phenotypes of ancestors. We developed HAPI-RECAP, a method that reconstructs the DNA of parents from full siblings and their relatives. This tool leverages HAPI2's output, a new phasing approach that applies to siblings (and optionally one or both parents) and reliably infers parent haplotypes but does not link the ungenotyped parents' DNA across chromosomes or between segments flanking ambiguities. By combining IBD between the reconstructed parents and the relatives, HAPI-RECAP resolves the source parent of these segments. Moreover, the method exploits crossovers the children inherited and sex-specific genetic maps to infer the reconstructed parents' sexes. We validated these methods on research participants from both 23andMe, Inc. and the San Antonio Mexican American Family Studies. Given data for one parent, HAPI2 reconstructs large fractions of the missing parent's DNA, between 77.6% and 99.97% among all families, and 90.3% on average in three- and four-child families. When reconstructing both parents, HAPI-RECAP inferred between 33.2% and 96.6% of the parents' genotypes, averaging 70.6% in four-child families. Reconstructed genotypes have average error rates < 10-3, or comparable to those from direct genotyping. HAPI-RECAP inferred the parent sexes 100% correctly given IBD-linked segments and can also reconstruct parents without any IBD. As datasets grow in size, more families will be implicitly collected; HAPI-RECAP holds promise to enable high quality parent genotype reconstruction.

Biobank-scale inference of multi-individual identity by descent and gene conversion

We present a method for efficiently identifying clusters of identical-by-descent haplotypes in biobank-scale sequence data. Our multi-individual approach enables much more computationally efficient inference of identity by descent (IBD) than approaches that infer pairwise IBD segments and provides locus-specific IBD clusters rather than IBD segments. Our method's computation time, memory requirements, and output size scale linearly with the number of individuals in the dataset. We also present a method for using multi-individual IBD to detect alleles changed by gene conversion. Application of our methods to the autosomal sequence data for 125,361 White British individuals in the UK Biobank detects more than 9 million converted alleles. This is 2,900 times more alleles changed by gene conversion than were detected in a previous analysis of familial data. We estimate that more than 250,000 sequenced probands and a much larger number of additional genomes from multi-generational family members would be required to find a similar number of alleles changed by gene conversion using a family-based approach. Our IBD clustering method is implemented in the open-source ibd-cluster software package.

Characterizing identity by descent segments in Chinese interpopulation unrelated individual pairs

Identity by descent (IBD) segments, uninterrupted DNA segments derived from the same ancestral chromosomes, are widely used as indicators of relationships in genetics. A great deal of research focuses on IBD segments between related pairs, while the statistical analyses of segments in irrelevant individuals are rare. In this study, we investigated the basic informative features of IBD segments in unrelated pairs in Chinese populations from the 1000 Genome Project. A total of 5922 IBD segments in Chinese interpopulation unrelated individual pairs were detected via IBIS and the average length of IBD was 3.71 Mb in length. It was found that 17.86% of unrelated pairs shared at least one IBD segment in the Chinese cohort. Furthermore, a total of 49 chromosomal regions where IBD segments clustered in high abundance were identified, which might be sharing hotspots in the human genome. Such regions could also be observed in other ancestry populations, which implies that similar IBD backgrounds also exist. Altogether, these results demonstrated the distribution of common background IBD segments, which helps improve the accuracy in pedigree studies based on IBD analysis.

Assessing the individual risk of stroke in caregivers of patients with stroke

BACKGROUND

 Genetic factors influence the risk of developing stroke. Still, it is unclear whether this risk is intrinsically high in certain people or if nongenetic factors explain it entirely.

OBJECTIVE

 To compare the risk of stroke in kin and nonkin caregivers.

METHODS

 In a cross-sectional study using the Stroke Riskometer app (AUT Ventures Limited, Auckland, AUK, New Zealand), we determined the 5- and 10-year stroke risk (SR) among caregivers of stroke inpatients. The degree of kinship was rated with a score ranging from 0 to 50 points.

RESULTS

 We studied 278 caregivers (69.4% of them female) with a mean age of 47.5 ± 14.2 years. Kin caregivers represented 70.1% of the sample, and 49.6% of them were offspring. The median SR at 5 years was of 2.1 (range: 0.35-17.3) versus 1.73 (range: 0.04-29.9), and of 4.0 (range: 0.45-38.6) versus 2.94 (range: 0.05-59.35) at 10 years for the nonkin and kin caregivers respectively. In linear logistic regression controlled for the age of the caregivers, adding the kinship score did not increase the overall variability of the model for the risk at 5 years (R2 = 0.271; p = 0.858) nor the risk at 10 years (R2 = 0.376; p = 0.78).

CONCLUSION

 Caregivers of stroke patients carry a high SR regardless of their degree of kinship.

Patterns of admixture and introgression in a mosaic Mytilus galloprovincialis and Mytilus edulis hybrid zone in SW England

The study of hybrid zones offers important insights into speciation. Earlier studies on hybrid populations of the marine mussel species Mytilus edulis and Mytilus galloprovincialis in SW England provided evidence of admixture but were constrained by the limited number of molecular markers available. We use 57 ancestry-informative SNPs, most of which have been mapped genetically, to provide evidence of distinctive differences between admixed populations in SW England and asymmetrical introgression from M. edulis to M. galloprovincialis. We combine the genetic study with analysis of phenotypic traits of potential ecological and adaptive significance. We demonstrate that hybrid individuals have brown mantle edges unlike the white or purple in the parental species, suggesting allelic or non-allelic genomic interactions. We report differences in gonad development stage between the species consistent with a prezygotic barrier between the species. By incorporating results from publications dating back to 1980, we confirm the long-term stability of the hybrid zone despite higher viability of M. galloprovincialis. This stability coincides with a dramatic change in temperature of UK coastal waters and suggests that these hybrid populations might be resisting the effects of global warming. However, a single SNP locus associated with the Notch transmembrane signalling protein shows a markedly different pattern of variation to the others and might be associated with adaptation of M. galloprovincialis to colder northern temperatures.

Analysis of rare Parkinson's disease variants in millions of people

Although many rare variants have been reportedly associated with Parkinson's disease (PD), many have not been replicated or have failed to replicate. Here, we conduct a large-scale replication of rare PD variants. We assessed a total of 27,590 PD cases, 6701 PD proxies, and 3,106,080 controls from three data sets: 23andMe, Inc., UK Biobank, and AMP-PD. Based on well-known PD genes, 834 variants of interest were selected from the ClinVar annotated 23andMe dataset. We performed a meta-analysis using summary statistics of all three studies. The meta-analysis resulted in five significant variants after Bonferroni correction, including variants in GBA1 and LRRK2. Another eight variants are strong candidate variants for their association with PD. Here, we provide the largest rare variant meta-analysis to date, providing information on confirmed and newly identified variants for their association with PD using several large databases. Additionally we also show the complexities of studying rare variants in large-scale cohorts.

Biobank-scale inference of multi-individual identity by descent and gene conversion

We present a method for efficiently identifying clusters of identical-by-descent haplotypes in biobank-scale sequence data. Our multi-individual approach enables much more efficient collection and storage of identity by descent (IBD) information than approaches that detect and store pairwise IBD segments. Our method's computation time, memory requirements, and output size scale linearly with the number of individuals in the dataset. We also present a method for using multi-individual IBD to detect alleles changed by gene conversion. Application of our methods to the autosomal sequence data for 125,361 White British individuals in the UK Biobank detects more than 9 million converted alleles. This is 2900 times more alleles changed by gene conversion than were detected in a previous analysis of familial data. We estimate that more than 250,000 sequenced probands and a much larger number of additional genomes from multi-generational family members would be required to find a similar number of alleles changed by gene conversion using a family-based approach.

Influence of autozygosity on common disease risk across the phenotypic spectrum

Autozygosity is associated with rare Mendelian disorders and clinically relevant quantitative traits. We investigated associations between the fraction of the genome in runs of homozygosity (FROH) and common diseases in Genes & Health (n = 23,978 British South Asians), UK Biobank (n = 397,184), and 23andMe. We show that restricting analysis to offspring of first cousins is an effective way of reducing confounding due to social/environmental correlates of FROH. Within this group in G&H+UK Biobank, we found experiment-wide significant associations between FROH and twelve common diseases. We replicated associations with type 2 diabetes (T2D) and post-traumatic stress disorder via within-sibling analysis in 23andMe (median n = 480,282). We estimated that autozygosity due to consanguinity accounts for 5%-18% of T2D cases among British Pakistanis. Our work highlights the possibility of widespread non-additive genetic effects on common diseases and has important implications for global populations with high rates of consanguinity.

Genome-Wide Association Studies of Coffee Intake in UK/US Participants of European Ancestry Uncover Gene-Cohort Influences

Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N=130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across thousands of biomarkers and health and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from UK Biobank (UKB; N=334,659). The results of these two GWAS were highly discrepant. We observed positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in UKB. Genetic correlations with cognition were negative in 23andMe but positive in UKB. The only consistent observations were positive genetic correlations with substance use and obesity. Our study shows that GWAS in different cohorts could capture cultural differences in the relationship between behavior and genetics.

A cost-benefit analysis for use of large SNP panels and high throughput typing for forensic investigative genetic genealogy

Next-generation sequencing (NGS), also known as massively sequencing, enables large dense SNP panel analyses which generate the genetic component of forensic investigative genetic genealogy (FIGG). While the costs of implementing large SNP panel analyses into the laboratory system may seem high and daunting, the benefits of the technology may more than justify the investment. To determine if an infrastructural investment in public laboratories and using large SNP panel analyses would reap substantial benefits to society, a cost-benefit analysis (CBA) was performed. This CBA applied the logic that an increase of DNA profile uploads to a DNA database due to a sheer increase in number of markers and a greater sensitivity of detection afforded with NGS and a higher hit/association rate due to large SNP/kinship resolution and genealogy will increase investigative leads, will be more effective for identifying recidivists which in turn reduces future victims of crime, and will bring greater safety and security to communities. Analyses were performed for worst case/best case scenarios as well as by simulation sampling the range spaces with multiple input values simultaneously to generate best estimate summary statistics. This study shows that the benefits, both tangible and intangible, over the lifetime of an advanced database system would be huge and can be projected to be for less than $1 billion per year (over a 10-year period) investment can reap on average > $4.8 billion in tangible and intangible cost-benefits per year. More importantly, on average > 50,000 individuals need not become victims if FIGG were employed, assuming investigative associations generated were acted upon. The benefit to society is immense making the laboratory investment a nominal cost. The benefits likely are underestimated herein. There is latitude in the estimated costs, and even if they were doubled or tripled, there would still be substantial benefits gained with a FIGG-based approach. While the data used in this CBA are US centric (primarily because data were readily accessible), the model is generalizable and could be used by other jurisdictions to perform relevant and representative CBAs.

Disease risk and healthcare utilization among ancestrally diverse groups in the Los Angeles region

An individual's disease risk is affected by the populations that they belong to, due to shared genetics and environmental factors. The study of fine-scale populations in clinical care is important for identifying and reducing health disparities and for developing personalized interventions. To assess patterns of clinical diagnoses and healthcare utilization by fine-scale populations, we leveraged genetic data and electronic medical records from 35,968 patients as part of the UCLA ATLAS Community Health Initiative. We defined clusters of individuals using identity by descent, a form of genetic relatedness that utilizes shared genomic segments arising due to a common ancestor. In total, we identified 376 clusters, including clusters with patients of Afro-Caribbean, Puerto Rican, Lebanese Christian, Iranian Jewish and Gujarati ancestry. Our analysis uncovered 1,218 significant associations between disease diagnoses and clusters and 124 significant associations with specialty visits. We also examined the distribution of pathogenic alleles and found 189 significant alleles at elevated frequency in particular clusters, including many that are not regularly included in population screening efforts. Overall, this work progresses the understanding of health in understudied communities and can provide the foundation for further study into health inequities.

RaPID-Query for fast identity by descent search and genealogical analysis

MOTIVATION

Due to the rapid growth of the genetic database size, genealogical search, a process of inferring familial relatedness by identifying DNA matches, has become a viable approach to help individuals finding missing family members or law enforcement agencies locating suspects. A fast and accurate method is needed to search an out-of-database individual against millions of individuals. Most existing approaches only offer all-versus-all within panel match. Some prototype algorithms offer one-versus-all query from out-of-panel individual, but they do not tolerate errors.

RESULTS

A new method, random projection-based identity-by-descent (IBD) detection (RaPID) query, is introduced to make fast genealogical search possible. RaPID-Query identifies IBD segments between a query haplotype and a panel of haplotypes. By integrating matches over multiple PBWT indexes, RaPID-Query manages to locate IBD segments quickly with a given cutoff length while allowing mismatched sites. A single query against all UK biobank autosomal chromosomes was completed within 2.76 seconds on average, with the minimum length 7 cM and 700 markers. RaPID-Query achieved a 0.016 false negative rate and a 0.012 false positive rate simultaneously on a chromosome 20 sequencing panel having 86 265 sites. This is comparable to the state-of-the-art IBD detection method TPBWT(out-of-sample) and Hap-IBD. The high-quality IBD segments yielded by RaPID-Query were able to distinguish up to fourth degree of the familial relatedness for a given individual pair, and the area under the receiver operating characteristic curve values are at least 97.28%.

AVAILABILITY AND IMPLEMENTATION

The RaPID-Query program is available at https://github.com/ucfcbb/RaPID-Query.

Addressing the feasibility of people of African descent finding living African relatives using direct-to-consumer genetic testing

People of African descent use direct-to-consumer genomics services such as 23andMe and AncestryDNA for various family histories and health reasons, including identifying and interacting with the previously unknown living African genetic relatives. In this commentary, I argue that it is reasonable to consider that cousin pairs consisting of an African person and a descendant of an African person enslaved in the Americans during the Transatlantic Slave Trade (i.e., a person of African descent) have genealogical ancestors recent enough to be detected using autosomal DNA testing where the pair has shared ancestors in the range of 20-6 generations ago from the present.

Genome-wide Association Identifies Novel Etiological Insights Associated with Parkinson's Disease in African and African Admixed Populations

Background

Understanding the genetic mechanisms underlying diseases in ancestrally diverse populations is a critical step towards the realization of the global application of precision medicine. The African and African admixed populations enable mapping of complex traits given their greater levels of genetic diversity, extensive population substructure, and distinct linkage disequilibrium patterns.

Methods

Here we perform a comprehensive genome-wide assessment of Parkinson's disease (PD) in 197,918 individuals (1,488 cases; 196,430 controls) of African and African admixed ancestry, characterizing population-specific risk, differential haplotype structure and admixture, coding and structural genetic variation and polygenic risk profiling.

Findings

We identified a novel common risk factor for PD and age at onset at the GBA1 locus (risk, rs3115534-G; OR=1.58, 95% CI = 1.37 - 1.80, P=2.397E-14; age at onset, BETA =-2.004, SE =0.57, P = 0.0005), that was found to be rare in non-African/African admixed populations. Downstream short- and long-read whole genome sequencing analyses did not reveal any coding or structural variant underlying the GWAS signal. However, we identified that this signal mediates PD risk via expression quantitative trait locus (eQTL) mechanisms. While previously identified GBA1 associated disease risk variants are coding mutations, here we suggest a novel functional mechanism consistent with a trend in decreasing glucocerebrosidase activity levels. Given the high population frequency of the underlying signal and the phenotypic characteristics of the homozygous carriers, we hypothesize that this variant may not cause Gaucher disease. Additionally, the prevalence of Gaucher's disease in Africa is low.

Interpretation

The present study identifies a novel African-ancestry genetic risk factor in GBA1 as a major mechanistic basis of PD in the African and African admixed populations. This striking result contrasts to previous work in Northern European populations, both in terms of mechanism and attributable risk. This finding highlights the importance of understanding population-specific genetic risk in complex diseases, a particularly crucial point as the field moves toward precision medicine in PD clinical trials and while recognizing the need for equitable inclusion of ancestrally diverse groups in such trials. Given the distinctive genetics of these underrepresented populations, their inclusion represents a valuable step towards insights into novel genetic determinants underlying PD etiology. This opens new avenues towards RNA-based and other therapeutic strategies aimed at reducing lifetime risk.

Research in Context

Evidence Before this Study

Our current understanding of Parkinson's disease (PD) is disproportionately based on studying populations of European ancestry, leading to a significant gap in our knowledge about the genetics, clinical characteristics, and pathophysiology in underrepresented populations. This is particularly notable in individuals of African and African admixed ancestries. Over the last two decades, we have witnessed a revolution in the research area of complex genetic diseases. In the PD field, large-scale genome-wide association studies in the European, Asian, and Latin American populations have identified multiple risk loci associated with disease. These include 78 loci and 90 independent signals associated with PD risk in the European population, nine replicated loci and two novel population-specific signals in the Asian population, and a total of 11 novel loci recently nominated through multi-ancestry GWAS efforts.Nevertheless, the African and African admixed populations remain completely unexplored in the context of PD genetics.

Added Value of this Study

To address the lack of diversity in our research field, this study aimed to conduct the first genome-wide assessment of PD genetics in the African and African admixed populations. Here, we identified a genetic risk factor linked to PD etiology, dissected African-specific differences in risk and age at onset, characterized known genetic risk factors, and highlighted the utility of the African and African admixed risk haplotype substructure for future fine-mapping efforts. We identified a novel disease mechanism via expression changes consistent with decreased GBA1 activity levels. Future large scale single cell expression studies should investigate the neuronal populations in which expression differences are most prominent. This novel mechanism may hold promise for future efficient RNA-based therapeutic strategies such as antisense oligonucleotides or short interfering RNAs aimed at preventing and decreasing disease risk. We envisage that these data generated under the umbrella of the Global Parkinson's Genetics Program (GP2) will shed light on the molecular mechanisms involved in the disease process and might pave the way for future clinical trials and therapeutic interventions. This work represents a valuable resource in an underserved population, supporting pioneering research within GP2 and beyond. Deciphering causal and genetic risk factors in all these ancestries will help determine whether interventions, potential targets for disease modifying treatment, and prevention strategies that are being studied in the European populations are relevant to the African and African admixed populations.

Implications of all the Available Evidence

We nominate a novel signal impacting GBA1 as the major genetic risk factor for PD in the African and African admixed populations. The present study could inform future GBA1 clinical trials, improving patient stratification. In this regard, genetic testing can help to design trials likely to provide meaningful and actionable answers. It is our hope that these findings may ultimately have clinical utility for this underrepresented population.

Development of a novel microarray data analysis tool without normalization for genotyping degraded forensic DNA

Since the arrest of the Golden State Killer in the US in April 2018, forensic geneticists have been increasingly interested in the investigative genetic genealogy (IGG) method. While this method has already been in practical use as a powerful tool for criminal investigation, we have yet to know well the limitations and potential risks. In this current study, we performed an evaluation study focusing on degraded DNA using the Affymetrix Genome-Wide Human SNP Array 6.0 platform (Thermo Fisher Scientific). We revealed one of the potential problems that occur during SNP genotype determination using a microarray-based platform. Our analysis results indicated that the SNP profiles derived from degraded DNA contained many false heterozygous SNPs. In addition, it was confirmed that the total amount of probe signal intensity on microarray chips derived from degraded DNA decreased significantly. Because the conventional analysis algorithm performs normalization during genotype determination, we concluded that noise signals could be genotype-called. To address this issue, we proposed a novel microarray data analysis method without normalization (nMAP). Although the nMAP algorithm resulted in a low call rate, it substantially improved genotyping accuracy. Finally, we confirmed the usefulness of the nMAP algorithm for kinship inferences. These findings and the nMAP algorithm will make a contribution to the advance of the IGG method.

Guidelines for genetic ancestry inference created through roundtable discussions

The use of genetic and genomic technology to infer ancestry is commonplace in a variety of contexts, particularly in biomedical research and for direct-to-consumer genetic testing. In 2013 and 2015, two roundtables engaged a diverse group of stakeholders toward the development of guidelines for inferring genetic ancestry in academia and industry. This report shares the stakeholder groups' work and provides an analysis of, commentary on, and views from the groundbreaking and sustained dialogue. We describe the engagement processes and the stakeholder groups' resulting statements and proposed guidelines. The guidelines focus on five key areas: application of genetic ancestry inference, assumptions and confidence/laboratory and statistical methods, terminology and population identifiers, impact on individuals and groups, and communication or translation of genetic ancestry inferences. We delineate the terms and limitations of the guidelines and discuss their critical role in advancing the development and implementation of best practices for inferring genetic ancestry and reporting the results. These efforts should inform both governmental regulation and self-regulation.

GRAPE: genomic relatedness detection pipeline

Classifying the degree of relatedness between pairs of individuals has both scientific and commercial applications. As an example, genome-wide association studies (GWAS) may suffer from high rates of false positive results due to unrecognized population structure. This problem becomes especially relevant with recent increases in large-cohort studies. Accurate relationship classification is also required for genetic linkage analysis to identify disease-associated loci. Additionally, DNA relatives matching service is one of the leading drivers for the direct-to-consumer genetic testing market. Despite the availability of scientific and research information on the methods for determining kinship and the accessibility of relevant tools, the assembly of the pipeline, which stably operates on a real-world genotypic data, requires significant research and development resources. Currently, there is no open source end-to-end solution for relatedness detection in genomic data, that is fast, reliable and accurate for both close and distant degrees of kinship, combines all the necessary processing steps to work on a real data, and is ready for production integration. To address this, we developed GRAPE: Genomic RelAtedness detection PipelinE. It combines data preprocessing, identity-by-descent (IBD) segments detection, and accurate relationship estimation. The project uses software development best practices, as well as Global Alliance for Genomics and Health (GA4GH) standards and tools. Pipeline efficiency is demonstrated on both simulated and real-world datasets. GRAPE is available from: https://github.com/genxnetwork/grape.

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 14^th 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 14^th century and highlight late medieval genetic heterogeneity no longer present in modern AJ.

Open-source benchmarking of IBD segment detection methods for biobank-scale cohorts

In the recent biobank era of genetics, the problem of identical-by-descent (IBD) segment detection received renewed interest, as IBD segments in large cohorts offer unprecedented opportunities in the study of population and genealogical history, as well as genetic association of long haplotypes. While a new generation of efficient methods for IBD segment detection becomes available, direct comparison of these methods is difficult: existing benchmarks were often evaluated in different datasets, with some not openly accessible; methods benchmarked were run under suboptimal parameters; and benchmark performance metrics were not defined consistently. Here, we developed a comprehensive and completely open-source evaluation of the power, accuracy, and resource consumption of these IBD segment detection methods using realistic population genetic simulations with various settings. Our results pave the road for fair evaluation of IBD segment detection methods and provide an practical guide for users.

Accurate genome-wide phasing from IBD data

As genotype databases increase in size, so too do the number of detectable segments of identity by descent (IBD): segments of the genome where two individuals share an identical copy of one of their two parental haplotypes, due to shared ancestry. We show that given a large enough genotype database, these segments of IBD collectively overlap entire chromosomes, including instances of IBD that span multiple chromosomes, and can be used to accurately separate the alleles inherited from each parent across the entire genome. The resulting phase is not an improvement over state-of-the-art local phasing methods, but provides accurate long-range phasing that indicates which of two haplotypes in different regions of the genome, including different chromosomes, was inherited from the same parent. We are able to separate the DNA inherited from each parent completely, across the entire genome, with 98% median accuracy in a test set of 30,000 individuals. We estimate the IBD data requirements for accurate genome-wide phasing, and we propose a method for estimating confidence in the resulting phase. We show that our methods do not require the genotypes of close family, and that they are robust to genotype errors and missing data. In fact, our method can impute missing data accurately and correct genotype errors.

Evaluating the utility of identity-by-descent segment numbers for relatedness inference via information theory and classification

Despite decades of methods development for classifying relatives in genetic studies, pairwise relatedness methods' recalls are above 90% only for first through third-degree relatives. The top-performing approaches, which leverage identity-by-descent segments, often use only kinship coefficients, while others, including estimation of recent shared ancestry (ERSA), use the number of segments relatives share. To quantify the potential for using segment numbers in relatedness inference, we leveraged information theory measures to analyze exact (i.e. produced by a simulator) identity-by-descent segments from simulated relatives. Over a range of settings, we found that the mutual information between the relatives' degree of relatedness and a tuple of their kinship coefficient and segment number is on average 4.6% larger than between the degree and the kinship coefficient alone. We further evaluated identity-by-descent segment number utility by building a Bayes classifier to predict first through sixth-degree relationships using different feature sets. When trained and tested with exact segments, the inclusion of segment numbers improves the recall by between 0.28% and 3% for second through sixth-degree relatives. However, the recalls improve by less than 1.8% per degree when using inferred segments, suggesting limitations due to identity-by-descent detection accuracy. Last, we compared our Bayes classifier that includes segment numbers with both ERSA and IBIS and found comparable recalls, with the Bayes classifier and ERSA slightly outperforming each other across different degrees. Overall, this study shows that identity-by-descent segment numbers can improve relatedness inference, but errors from current SNP array-based detection methods yield dampened signals in practice.

Characterizing mood disorders in the AFFECT study: a large, longitudinal, and phenotypically rich genetic cohort in the US

There has recently been marked progress in identifying genetic risk factors for major depression (MD) and bipolar disorder (BD); however, few systematic efforts have been made to elucidate heterogeneity that exists within and across these diagnostic taxa. The Affective disorders, Environment, and Cognitive Trait (AFFECT) study presents an opportunity to identify and associate the structure of cognition and symptom-level domains across the mood disorder spectrum in a prospective study from a diverse US population.Participants were recruited from the 23andMe, Inc research participant database and through social media; self-reported diagnosis of MD or BD by a medical professional and medication status data were used to enrich for mood-disorder cases. Remote assessments were used to acquire an extensive range of phenotypes, including mood state, transdiagnostic symptom severity, task-based measures of cognition, environmental exposures, personality traits. In this paper we describe the study design, and the demographic and clinical characteristics of the cohort. In addition we report genetic ancestry, SNP heritability, and genetic correlations with other large cohorts of mood disorders.A total of 48,467 participants were enrolled: 14,768 with MD, 9864 with BD, and 23,835 controls. Upon enrollment, 47% of participants with MD and 27% with BD indicated being in an active mood episode. Cases reported early ages of onset (mean = 13.2 and 14.3 years for MD and BD, respectively), and high levels of recurrence (78.6% and 84.9% with >5 episodes), psychotherapy, and psychotropic medication use. SNP heritability on the liability scale for the ascertained MD participants (0.19-0.21) was consistent with the high level of disease severity in this cohort, while BD heritability estimates (0.16-0.22) were comparable to reports in other large scale genomic studies of mood disorders. Genetic correlations between the AFFECT cohort and other large-scale cohorts were high for MD but not for BD. By incorporating transdiagnostic symptom assessments, repeated measures, and genomic data, the AFFECT study represents a unique resource for dissecting the structure of mood disorders across multiple levels of analysis. In addition, the fully remote nature of the study provides valuable insights for future virtual and decentralized clinical trials within mood disorders.

The overview of forensic genetic genealogy

Forensic genetic genealogy (FGG) benefits largely from popularity of genealogical research within (mostly) American society and the advent of new sequencing techniques that allow typing of challenging forensic samples. It is considered a true breakthrough for both active and especially cold cases where all other resources and methods have failed during investigation. Despite media coverage generally highlighting its powers, the method itself is considered very laborious and the investigation may easily got suspended at every stage due to many factors including no hits in the database or breaks in traceable lineages within the family tree. This review summarizes the scope of FGG use, mentions most concerns and misconceptions associated with the technique and points to the plausible solutions already suggested. It also brings together current guidelines and regulations intended to be followed by law enforcement authorities wishing to utilize genetic genealogy research.

Streamlining the decision-making process for international DNA kinship matching using Worldwide allele frequencies and tailored cutoff log10LR thresholds

The identification of human remains belonging to missing persons is one of the main challenges for forensic genetics. Although other means of identification can be applied to missing person investigations, DNA is often extremely valuable to further support or refute potential associations. When reference DNA samples cannot be collected from personal items belonging to a missing person, a direct DNA identification cannot be carried out. However, identifications can be made indirectly using DNA from the missing person's relatives. The ranking of likelihood ratio (LR) values, which measure the fit of a missing person for any given pedigree, is often the first step in selecting candidates in a DNA database. Although implementing DNA kinship matching in a national environment is feasible, many challenges need to be resolved before applying this method to an international configuration. In this study, we present an innovative and intuitive method to perform international DNA kinship matching and facilitate the comparison of DNA profiles when the ancestry is unknown or unsure and/or when different marker sets are used. This straightforward method, which is based on calculations performed with the DNA matching software BONAPARTE, Worldwide allele frequencies and tailored cutoff log₁₀LR thresholds, allows for the classification of potential candidates according to the strength of the DNA evidence and the predicted proportion of adventitious matches. This is a powerful method for streamlining the decision-making process in missing person investigations and DVI processes, especially when there are low numbers of overlapping typed STRs. Intuitive interpretation tables and a decision tree will help strengthen international data comparison for the identification of reported missing individuals discovered outside their national borders.

Impact of SNP microarray analysis of compromised DNA on kinship classification success in the context of investigative genetic genealogy

Single nucleotide polymorphism (SNP) data generated with microarray technologies have been used to solve murder cases via investigative leads obtained from identifying relatives of the unknown perpetrator included in accessible genomic databases, an approach referred to as investigative genetic genealogy (IGG). However, SNP microarrays were developed for relatively high input DNA quantity and quality, while DNA typically obtainable from crime scene stains is of low DNA quantity and quality, and SNP microarray data obtained from compromised DNA are largely missing. By applying the Illumina Global Screening Array (GSA) to 264 DNA samples with systematically altered quantity and quality, we empirically tested the impact of SNP microarray analysis of compromised DNA on kinship classification success, as relevant in IGG. Reference data from manufacturer-recommended input DNA quality and quantity were used to estimate genotype accuracy in the compromised DNA samples and for simulating data of different degree relatives. Although stepwise decrease of input DNA amount from 200 ng to 6.25 pg led to decreased SNP call rates and increased genotyping errors, kinship classification success did not decrease down to 250 pg for siblings and 1st cousins, 1 ng for 2nd cousins, while at 25 pg and below kinship classification success was zero. Stepwise decrease of input DNA quality via increased DNA fragmentation resulted in the decrease of genotyping accuracy as well as kinship classification success, which went down to zero at the average DNA fragment size of 150 base pairs. Combining decreased DNA quantity and quality in mock casework and skeletal samples further highlighted possibilities and limitations. Overall, GSA analysis achieved maximal kinship classification success from 800 to 200 times lower input DNA quantities than manufacturer-recommended, although DNA quality plays a key role too, while compromised DNA produced false negative kinship classifications rather than false positive ones.

Bonsai: An efficient method for inferring large human pedigrees from genotype data

Pedigree inference from genotype data is a challenging problem, particularly when pedigrees are sparsely sampled and individuals may be distantly related to their closest genotyped relatives. We present a method that infers small pedigrees of close relatives and then assembles them into larger pedigrees. To assemble large pedigrees, we introduce several formulas and tools including a likelihood for the degree separating two small pedigrees, a generalization of the fast DRUID point estimate of the degree separating two pedigrees, a method for detecting individuals who share background identity-by-descent (IBD) that does not reflect recent common ancestry, and a method for identifying the ancestral branches through which distant relatives are connected. Our method also takes several approaches that help to improve the accuracy and efficiency of pedigree inference. In particular, we incorporate age information directly into the likelihood rather than using ages only for consistency checks and we employ a heuristic branch-and-bound-like approach to more efficiently explore the space of possible pedigrees. Together, these approaches make it possible to construct large pedigrees that are challenging or intractable for current inference methods.

Current Developments in Detection of Identity-by-Descent Methods and Applications

Identity-by-descent (IBD), the detection of shared segments inherited from a common ancestor, is a fundamental concept in genomics with broad applications in the characterization and analysis of genomes. While historically the concept of IBD was extensively utilized through linkage analyses and in studies of founder populations, applications of IBD-based methods subsided during the genome-wide association study era. This was primarily due to the computational expense of IBD detection, which becomes increasingly relevant as the field moves toward the analysis of biobank-scale datasets that encompass individuals from highly diverse backgrounds. To address these computational barriers, the past several years have seen new methodological advances enabling IBD detection for datasets in the hundreds of thousands to millions of individuals, enabling novel analyses at an unprecedented scale. Here, we describe the latest innovations in IBD detection and describe opportunities for the application of IBD-based methods across a broad range of questions in the field of genomics.

Estimating heritability and its enrichment in tissue-specific gene sets in admixed populations

It is important to study the genetics of complex traits in diverse populations. Here, we introduce covariate-adjusted linkage disequilibrium (LD) score regression (cov-LDSC), a method to estimate SNP-heritability (${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}})$ and its enrichment in homogenous and admixed populations with summary statistics and in-sample LD estimates. In-sample LD can be estimated from a subset of the genome-wide association studies samples, allowing our method to be applied efficiently to very large cohorts. In simulations, we show that unadjusted LDSC underestimates ${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$ by 10-60% in admixed populations; in contrast, cov-LDSC is robustly accurate. We apply cov-LDSC to genotyping data from 8124 individuals, mostly of admixed ancestry, from the Slim Initiative in Genomic Medicine for the Americas study, and to approximately 161 000 Latino-ancestry individuals, 47 000 African American-ancestry individuals and 135 000 European-ancestry individuals, as classified by 23andMe. We estimate ${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$ and detect heritability enrichment in three quantitative and five dichotomous phenotypes, making this, to our knowledge, the most comprehensive heritability-based analysis of admixed individuals to date. Most traits have high concordance of ${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$ and consistent tissue-specific heritability enrichment among different populations. However, for age at menarche, we observe population-specific heritability estimates of ${\boldsymbol{h}}_{\boldsymbol{g}}^{\mathbf{2}}$. We observe consistent patterns of tissue-specific heritability enrichment across populations; for example, in the limbic system for BMI, the per-standardized-annotation effect size $ \tau $* is 0.16 ± 0.04, 0.28 ± 0.11 and 0.18 ± 0.03 in the Latino-, African American- and European-ancestry populations, respectively. Our approach is a powerful way to analyze genetic data for complex traits from admixed populations.

Rapid detection of identity-by-descent tracts for mega-scale datasets

The ability to identify segments of genomes identical-by-descent (IBD) is a part of standard workflows in both statistical and population genetics. However, traditional methods for finding local IBD across all pairs of individuals scale poorly leading to a lack of adoption in very large-scale datasets. Here, we present iLASH, an algorithm based on similarity detection techniques that shows equal or improved accuracy in simulations compared to current leading methods and speeds up analysis by several orders of magnitude on genomic datasets, making IBD estimation tractable for millions of individuals. We apply iLASH to the PAGE dataset of ~52,000 multi-ethnic participants, including several founder populations with elevated IBD sharing, identifying IBD segments in ~3 minutes per chromosome compared to over 6 days for a state-of-the-art algorithm. iLASH enables efficient analysis of very large-scale datasets, as we demonstrate by computing IBD across the UK Biobank (~500,000 individuals), detecting 12.9 billion pairwise connections.

Getting the conclusive lead with investigative genetic genealogy - A successful case study of a 16 year old double murder in Sweden

On the morning of October 19, 2004, an eight-year-old boy and a 56-year-old woman were stabbed to death on an open street in the city of Linköping, Sweden. The perpetrator left his DNA at the crime scene, and after 15 years of various investigation efforts, including more than 9000 interrogations and mass DNA screening of more than 6000 men, there were still no clues about the identity of the unknown murderer. The successful application of investigative genetic genealogy (IGG) in the US raised the interest for this tool within the Swedish Police Authority. After legal consultations it was decided that IGG could be applied in this double murder case as a pilot case study. From extensive DNA analysis, including whole-genome sequencing and genotype imputation, DNA data sets were established and searched within both GEDmatch and FamilyTree DNA genealogy databases. A number of fairly distant relatives were found from which family trees were created. The genealogy work resulted in two candidates, two brothers, one of whom matched the crime scene samples by routine STR profiling. The suspect confessed the murders at the initial police hearing and was later convicted of the murders. In this paper we describe the successful application of an emerging technology. We disclose details of the DNA analyses which, due to the poor quality and low quantity of the DNA, required reiterative sequencing and genotype imputation efforts. The successful application of IGG in this double murder case exemplifies its applicability not only in the US but also in Europe. The pressure is now high on the involved authorities to establish IGG as a tool for cold case criminal investigations and for missing person identifications. There is, however, a continuous need to accommodate legal, social and ethical aspects as well.

Fast and Robust Identity-by-Descent Inference with the Templated Positional Burrows-Wheeler Transform

Estimating the genomic location and length of identical-by-descent (IBD) segments among individuals is a crucial step in many genetic analyses. However, the exponential growth in the size of biobank and direct-to-consumer genetic data sets makes accurate IBD inference a significant computational challenge. Here we present the templated positional Burrows-Wheeler transform (TPBWT) to make fast IBD estimates robust to genotype and phasing errors. Using haplotype data simulated over pedigrees with realistic genotyping and phasing errors, we show that the TPBWT outperforms other state-of-the-art IBD inference algorithms in terms of speed and accuracy. For each phase-aware method, we explore the false positive and false negative rates of inferring IBD by segment length and characterize the types of error commonly found. Our results highlight the fragility of most phased IBD inference methods; the accuracy of IBD estimates can be highly sensitive to the quality of haplotype phasing. Additionally, we compare the performance of the TPBWT against a widely used phase-free IBD inference approach that is robust to phasing errors. We introduce both in-sample and out-of-sample TPBWT-based IBD inference algorithms and demonstrate their computational efficiency on massive-scale data sets with millions of samples. Furthermore, we describe the binary file format for TPBWT-compressed haplotypes that results in fast and efficient out-of-sample IBD computes against very large cohort panels. Finally, we demonstrate the utility of the TPBWT in a brief empirical analysis, exploring geographic patterns of haplotype sharing within Mexico. Hierarchical clustering of IBD shared across regions within Mexico reveals geographically structured haplotype sharing and a strong signal of isolation by distance. Our software implementation of the TPBWT is freely available for noncommercial use in the code repository (https://github.com/23andMe/phasedibd, last accessed January 11, 2021).

Genetic analyses identify widespread sex-differential participation bias

Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of participation bias is challenging since it requires the genotypes of unseen individuals. Here we demonstrate that it is possible to estimate comparative biases by performing a genome-wide association study contrasting one subgroup versus another. For example, we showed that sex exhibits artifactual autosomal heritability in the presence of sex-differential participation bias. By performing a genome-wide association study of sex in approximately 3.3 million males and females, we identified over 158 autosomal loci spuriously associated with sex and highlighted complex traits underpinning differences in study participation between the sexes. For example, the body mass index-increasing allele at FTO was observed at higher frequency in males compared to females (odds ratio = 1.02, P = 4.4 × 10^-36). Finally, we demonstrated how these biases can potentially lead to incorrect inferences in downstream analyses and propose a conceptual framework for addressing such biases. Our findings highlight a new challenge that genetic studies may face as sample sizes continue to grow.

Genetic analyses identify widespread sex-differential participation bias

Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of participation bias is challenging since it requires the genotypes of unseen individuals. Here we demonstrate that it is possible to estimate comparative biases by performing a genome-wide association study contrasting one subgroup versus another. For example, we showed that sex exhibits artifactual autosomal heritability in the presence of sex-differential participation bias. By performing a genome-wide association study of sex in approximately 3.3 million males and females, we identified over 158 autosomal loci spuriously associated with sex and highlighted complex traits underpinning differences in study participation between the sexes. For example, the body mass index-increasing allele at FTO was observed at higher frequency in males compared to females (odds ratio = 1.02, P = 4.4 × 10^-36). Finally, we demonstrated how these biases can potentially lead to incorrect inferences in downstream analyses and propose a conceptual framework for addressing such biases. Our findings highlight a new challenge that genetic studies may face as sample sizes continue to grow.

Nuclear genome-wide associations with mitochondrial heteroplasmy

The role of the nuclear genome in maintaining the stability of the mitochondrial genome (mtDNA) is incompletely known. mtDNA sequence variants can exist in a state of heteroplasmy, which denotes the coexistence of organellar genomes with different sequences. Heteroplasmic variants that impair mitochondrial capacity cause disease, and the state of heteroplasmy itself is deleterious. However, mitochondrial heteroplasmy may provide an intermediate state in the emergence of novel mitochondrial haplogroups. We used genome-wide genotyping data from 982,072 European ancestry individuals to evaluate variation in mitochondrial heteroplasmy and to identify the regions of the nuclear genome that affect it. Age, sex, and mitochondrial haplogroup were associated with the extent of heteroplasmy. GWAS identified 20 loci for heteroplasmy that exceeded genome-wide significance. This included a region overlapping mitochondrial transcription factor A (TFAM), which has multiple roles in mtDNA packaging, replication, and transcription. These results show that mitochondrial heteroplasmy has a heritable nuclear component.

Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color

Human eye color is highly heritable, but its genetic architecture is not yet fully understood. We report the results of the largest genome-wide association study for eye color to date, involving up to 192,986 European participants from 10 populations. We identify 124 independent associations arising from 61 discrete genomic regions, including 50 previously unidentified. We find evidence for genes involved in melanin pigmentation, but we also find associations with genes involved in iris morphology and structure. Further analyses in 1636 Asian participants from two populations suggest that iris pigmentation variation in Asians is genetically similar to Europeans, albeit with smaller effect sizes. Our findings collectively explain 53.2% (95% confidence interval, 45.4 to 61.0%) of eye color variation using common single-nucleotide polymorphisms. Overall, our study outcomes demonstrate that the genetic complexity of human eye color considerably exceeds previous knowledge and expectations, highlighting eye color as a genetically highly complex human trait.

Investigative genetic genealogy: Current methods, knowledge and practice

Investigative genetic genealogy (IGG) has emerged as a new, rapidly growing field of forensic science. We describe the process whereby dense SNP data, commonly comprising more than half a million markers, are employed to infer distant relationships. By distant we refer to degrees of relatedness exceeding that of first cousins. We review how methods of relationship matching and SNP analysis on an enlarged scale are used in a forensic setting to identify a suspect in a criminal investigation or a missing person. There is currently a strong need in forensic genetics not only to understand the underlying models to infer relatedness but also to fully explore the DNA technologies and data used in IGG. This review brings together many of the topics and examines their effectiveness and operational limits, while suggesting future directions for their forensic validation. We further investigated the methods used by the major direct-to-consumer (DTC) genetic ancestry testing companies as well as submitting a questionnaire where providers of forensic genetic genealogy summarized their operation/services. Although most of the DTC market, and genetic genealogy in general, has undisclosed, proprietary algorithms we review the current knowledge where information has been discussed and published more openly.

Disease risk scores for skin cancers

We trained and validated risk prediction models for the three major types of skin cancer- basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma-on a cross-sectional and longitudinal dataset of 210,000 consented research participants who responded to an online survey covering personal and family history of skin cancer, skin susceptibility, and UV exposure. We developed a primary disease risk score (DRS) that combined all 32 identified genetic and non-genetic risk factors. Top percentile DRS was associated with an up to 13-fold increase (odds ratio per standard deviation increase >2.5) in the risk of developing skin cancer relative to the middle DRS percentile. To derive lifetime risk trajectories for the three skin cancers, we developed a second and age independent disease score, called DRSA. Using incident cases, we demonstrated that DRSA could be used in early detection programs for identifying high risk asymptotic individuals, and predicting when they are likely to develop skin cancer. High DRSA scores were not only associated with earlier disease diagnosis (by up to 14 years), but also with more severe and recurrent forms of skin cancer.

Distinguishing pedigree relationships via multi-way identity by descent sharing and sex-specific genetic maps

The proportion of samples with one or more close relatives in a genetic dataset increases rapidly with sample size, necessitating relatedness modeling and enabling pedigree-based analyses. Despite this, relatives are generally unreported and current inference methods typically detect only the degree of relatedness of sample pairs and not pedigree relationships. We developed CREST, an accurate and fast method that identifies the pedigree relationships of close relatives. CREST utilizes identity by descent (IBD) segments shared between a pair of samples and their mutual relatives, leveraging the fact that sharing rates among these individuals differ across pedigree configurations. Furthermore, CREST exploits the profound differences in sex-specific genetic maps to classify pairs as maternally or paternally related-e.g., paternal half-siblings-using the locations of autosomal IBD segments shared between the pair. In simulated data, CREST correctly classifies 91.5%-100% of grandparent-grandchild (GP) pairs, 80.0%-97.5% of avuncular (AV) pairs, and 75.5%-98.5% of half-siblings (HS) pairs compared to PADRE's rates of 38.5%-76.0% of GP, 60.5%-92.0% of AV, 73.0%-95.0% of HS pairs. Turning to the real 20,032 sample Generation Scotland (GS) dataset, CREST identified seven pedigrees with incorrect relationship types or maternal/paternal parent sexes, five of which we confirmed as mistakes, and two with uncertain relationships. After correcting these, CREST correctly determines relationship types for 93.5% of GP, 97.7% of AV, and 92.2% of HS pairs that have sufficient mutual relative data; the parent sex in 100% of HS and 99.6% of GP pairs; and it completes this analysis in 2.8 h including IBD detection in eight threads.

Genome-wide association study identifies 48 common genetic variants associated with handedness

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10-8) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (rG = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.

Unhealthy Behaviours and Risk of Parkinson's Disease: A Mendelian Randomisation Study

BACKGROUND

Tobacco smoking and alcohol intake have been identified in observational studies as potentially protective factors against developing Parkinson's disease (PD); the impact of body mass index (BMI) on PD risk is debated. Whether such epidemiological associations are causal remains unclear. Mendelian randomsation (MR) uses genetic variants to explore the effects of exposures on outcomes; potentially reducing bias from residual confounding and reverse causation.

OBJECTIVE

Using MR, we examined relationships between PD risk and three unhealthy behaviours: tobacco smoking, alcohol intake, and higher BMI.

METHODS

19,924 PD cases and 2,413,087 controls were included in the analysis. We performed genome-wide association studies to identify single nucleotide polymorphisms associated with tobacco smoking, alcohol intake, and BMI. MR analysis of the relationship between each exposure and PD was undertaken using a split-sample design.

RESULTS

Ever-smoking reduced the risk of PD (OR 0.955; 95%confidence interval [CI] 0.921-0.991; p = 0.013). Higher daily alcohol intake increased the risk of PD (OR 1.125, 95%CI 1.025-1.235; p = 0.013) and a 1 kg/m2 higher BMI reduced the risk of PD (OR 0.988, 95%CI 0.979-0.997; p = 0.008). Sensitivity analyses did not suggest bias from horizontal pleiotropy or invalid instruments.

CONCLUSION

Using split-sample MR in over 2.4 million participants, we observed a protective effect of smoking on risk of PD. In contrast to observational data, alcohol consumption appeared to increase the risk of PD. Higher BMI had a protective effect on PD, but the effect was small.

The association of clinical phenotypes to known AD/FTD genetic risk loci and their inter-relationship

To elucidate how variants in genetic risk loci previously implicated in Alzheimer’s Disease (AD) and/or frontotemporal dementia (FTD) contribute to expression of disease phenotypes, a phenome-wide association study was performed in two waves. In the first wave, we explored clinical traits associated with thirteen genetic variants previously reported to be linked to disease risk using both the 23andMe and UKB cohorts. We tested 30 additional AD variants in UKB cohort only in the second wave. APOE variants defining ε2/ε3/ε4 alleles and rs646776 were identified to be significantly associated with metabolic/cardiovascular and longevity traits. APOE variants were also significantly associated with neurological traits. ABI3 variant rs28394864 was significantly associated with cardiovascular (e.g. (hypertension, ischemic heart disease, coronary atherosclerosis, angina) and immune-related trait asthma. Both APOE variants and CLU variant were significantly associated with nearsightedness. HLA- DRB1 variant was associated with diseases with immune-related traits. Additionally, variants from 10+ AD genes (BZRAP1-AS1, ADAMTS4, ADAM10, APH1B, SCIMP, ABI3, SPPL2A, ZNF232, GRN, CD2AP, and CD33) were associated with hematological measurements such as white blood cell (leukocyte) count, monocyte count, neutrophill count, platelet count, and/or mean platelet (thrombocyte) volume (an autoimmune disease biomarker). Many of these genes are expressed specifically in microglia. The associations of ABI3 variant with cardiovascular and immune-related traits are one of the novel findings from this study. Taken together, it is evidenced that at least some AD and FTD variants are associated with multiple clinical phenotypes and not just dementia. These findings were discussed in the context of causal relationship versus pleiotropy via Mendelian randomization analysis.

Forensic investigation approaches of searching relatives in DNA databases

There are several indirect database searching approaches to identify the potential source of a forensic biological sample. These DNA-based approaches are familial searching, Y-STR database searching, and investigative genetic genealogy (IGG). The first two strategies use forensic DNA databases managed by the government, and the latter uses databases managed by private citizens or companies. Each of these search strategies relies on DNA testing to identify relatives of the donor of the crime scene sample, provided such profiles reside in the DNA database(s). All three approaches have been successfully used to identify the donor of biological evidence, which assisted in solving criminal cases or identifying unknown human remains. This paper describes and compares these approaches in terms of genotyping technologies, searching methods, database structures, searching efficiency, data quality, data security, and costs, and raises some potential privacy and legal considerations for further discussion by stakeholders and scientists. Y-STR database searching and IGG are advantageous since they are able to assist in more cases than familial searching readily identifying distant relatives. In contrast, familial searching can be performed more readily with existing laboratory systems. Every country or state may have its own unique economic, technical, cultural, and legal considerations and should decide the best approach(es) to fit those circumstances. Regardless of the approach, the ultimate goal should be the same: generate investigative leads and solve active and cold criminal cases to public safety, under stringent policies and security practices designed to protect the privacy of its citizenry.

Identification of a new genetic variant associated with cholecystitis: A multicenter genome-wide association study

BACKGROUND

The genomic landscape of gallbladder disease remains poorly understood. We sought to examine the association between genetic variants and the development of cholecystitis.

METHODS

The Biobank of a large multi-institutional health care system was used. All patients with cholecystitis were identified using International Statistical Classification of Diseases, 10th Revision, codes and genotyped across six batches. To control for population stratification, data were restricted to that from individuals of European genomic ancestry using a multidimensional scaling approach. The association between single nucleotide polymorphisms and cholecystitis was evaluated with a mixed linear model-based analysis, controlling for age, sex, and obesity. The threshold for significance was set at 5 × 10.

RESULTS

Of 24,635 patients (mean ± SD age, 60.1 ± 16.7 years; 13,022 females [52.9%]), 900 had cholecystitis (mean ± SD age, 65.4 ± 14.3 years; 496 females [55.1%]). After meta-analysis, three single nucleotide polymorphisms on chromosome 5p15 exceeded the threshold for significance (p < 5 × 10). The phenotypic variance of cholecystitis explained by genetics and controlling for sex and obesity was estimated to be 17.9%.

CONCLUSION

Using a multi-institutional genomic Biobank, we report that a region on chromosome 5p15 is associated with the development of cholecystitis that can be used to identify patients at risk.

LEVEL OF EVIDENCE

Prognostic and epidemiological, Level III.

Pedigrees and Perpetrators: Uses of DNA and Genealogy in Forensic Investigations

In the past few years, cases with DNA evidence that could not be solved with direct matches in DNA databases have benefited from comparing single-nucleotide polymorphism data with private and public genomic databases. Using a combination of genome comparisons and traditional genealogical research, investigators can triangulate distant relatives to the contributor of DNA data from a crime scene, ultimately identifying perpetrators of violent crimes. This approach has also been successful in identifying unknown deceased persons and perpetrators of lesser crimes. Such advances are bringing into focus ethical questions on how much access to DNA databases should be granted to law enforcement and how best to empower public genome contributors with control over their data. The necessary policies will take time to develop but can be informed by reflection on the familial searching policies developed for searches of the federal DNA database and considerations of the anonymity and privacy interests of civilians.