A survey of direct-to-consumer genotype data, and quality control tool (GenomePrep) for research

Identifying individuals with rare disease variants by inferring shared ancestral haplotypes from SNP array data

We describe FoundHaplo, an identity-by-descent algorithm that can be used to screen untyped disease-causing variants using single nucleotide polymorphism (SNP) array data. FoundHaplo leverages knowledge of shared disease haplotypes for inherited variants to identify those who share the disease haplotype and are, therefore, likely to carry the rare [minor allele frequency (MAF) ≤ 0.01%] variant. We performed a simulation study to evaluate the performance of FoundHaplo across 33 disease-harbouring loci. FoundHaplo was used to infer the presence of two rare (MAF ≤ 0.01%) pathogenic variants, SCN1B c.363C>G (p.Cys121Trp) and WWOX c.49G>A (p.E17K), which can cause mild dominant and severe recessive epilepsy, respectively, in the Epi25 cohort and the UK Biobank. FoundHaplo demonstrated substantially better sensitivity at inferring the presence of these rare variants than existing genome-wide imputation. FoundHaplo is a valuable screening tool for searching disease-causing variants with known founder effects using only SNP genotyping data. It is also applicable to nonhuman applications and nondisease-causing traits, including rare-variant drivers of quantitative traits. The FoundHaplo algorithm is available at https://github.com/bahlolab/FoundHaplo (DOI:10.5281/zenodo.8058286).

Forensic investigative genetic genealogy: expanding pedigree tracing and genetic inquiry in the genomic era

Genetic genealogy provides crucial insights into the complex biological relationships within contemporary and ancient human populations by analyzing shared alleles and chromosomal segments that are identical by descent to understand kinship, migration patterns, and population dynamics. Within forensic science, forensic investigative genetic genealogy (FIGG) has gained prominence by leveraging next-generation sequencing technologies and population-specific genomic resources, opening useful investigative avenues. In this review, we synthesize current knowledge, underscore recent advancements, and discuss the growing role of FIGG in forensic genomics. FIGG has been pivotal in revitalizing dormant inquiries and offering genetic leads in numerous cold cases. Its effectiveness relies on the extensive single-nucleotide polymorphism profiles contributed by individuals from diverse populations to specialized genomic databases. Advances in computational genomics and the growth of human genomic databases have spurred a profound shift in the application of genetic genealogy across forensics, anthropology, and ancient DNA studies. As the field progresses, FIGG is evolving from a nascent practice into a more sophisticated and specialized discipline, shaping the future of forensic investigations.

It's all relative: A multi-generational study using ForenSeq™ Kintelligence

The successful application of Forensic Investigative Genetic Genealogy (FIGG) to the identification of unidentified human remains and perpetrators of serious crime has led to a growing interest in its use internationally, including Australia. Routinely, FIGG has relied on the generation of high-density single nucleotide polymorphism (SNP) profiles from forensic samples using whole genome array (WGA) (∼650,000 or more SNPs) or whole genome sequencing (WGS) (millions of SNPs) for DNA segment-based comparisons in commercially available genealogy databases. To date, this approach has required DNA of a quality and quantity that is often not compatible with forensic samples. Furthermore, it requires the management of large data sets that include SNPs of medical relevance. The ForenSeq™ Kintelligence kit, comprising of 10,230 SNPs including 9867 for kinship association, was designed to overcome these challenges using a targeted amplicon sequencing-based method developed for low DNA inputs, inhibited and/or degraded forensic samples. To assess the ability of the ForenSeq™ Kintelligence workflow to correctly predict biological relationships, a comparative study comprising of 12 individuals from a family (with varying degrees of relatedness from 1st to 6th degree relatives) was undertaken using ForenSeq™ Kintelligence and a WGA approach using the Illumina Global Screening Array-24 version 3.0 Beadchip. All expected 1st, 2nd, 3rd, 4th and 5th degree relationships were correctly predicted using ForenSeq™ Kintelligence, while the expected 6th degree relationships were not detected. Given the (often) limited availability of forensic samples, findings from this study will assist Australian Law enforcement and other agencies considering the use of FIGG, to determine if the ForenSeq™ Kintelligence is suitable for existing workflows and casework sample types considered for FIGG.

Assessing Privacy Vulnerabilities in Genetic Data Sets: Scoping Review

BACKGROUND

Genetic data are widely considered inherently identifiable. However, genetic data sets come in many shapes and sizes, and the feasibility of privacy attacks depends on their specific content. Assessing the reidentification risk of genetic data is complex, yet there is a lack of guidelines or recommendations that support data processors in performing such an evaluation.

OBJECTIVE

This study aims to gain a comprehensive understanding of the privacy vulnerabilities of genetic data and create a summary that can guide data processors in assessing the privacy risk of genetic data sets.

METHODS

We conducted a 2-step search, in which we first identified 21 reviews published between 2017 and 2023 on the topic of genomic privacy and then analyzed all references cited in the reviews (n=1645) to identify 42 unique original research studies that demonstrate a privacy attack on genetic data. We then evaluated the type and components of genetic data exploited for these attacks as well as the effort and resources needed for their implementation and their probability of success.

RESULTS

From our literature review, we derived 9 nonmutually exclusive features of genetic data that are both inherent to any genetic data set and informative about privacy risk: biological modality, experimental assay, data format or level of processing, germline versus somatic variation content, content of single nucleotide polymorphisms, short tandem repeats, aggregated sample measures, structural variants, and rare single nucleotide variants.

CONCLUSIONS

On the basis of our literature review, the evaluation of these 9 features covers the great majority of privacy-critical aspects of genetic data and thus provides a foundation and guidance for assessing genetic data risk.

Genetic Risk Prediction for Prostate Cancer: Implications for Early Detection and Prevention

CONTEXT

Prostate cancer (PCa) is a leading cause of death and partially heritable. Genetic risk prediction might be useful for strategies to reduce PCa mortality through early detection and prevention.

OBJECTIVE

To review evidence for genetic risk prediction for PCa.

EVIDENCE ACQUISITION

A collaborative literature review was conducted using PubMed and Google Scholar. Search terms included genetic, risk, prediction, and "prostate cancer". Articles addressing screening, early detection, or prevention were prioritized, as were studies involving diverse populations.

EVIDENCE SYNTHESIS

Rare pathogenic mutations (RPMs), especially in DNA damage repair genes, increase PCa risk. RPMs in BRCA2 are most clearly deleterious, conferring 2-8.6 times higher risk of PCa and a higher risk of aggressive disease. Common genetic variants can be combined into genetic risk scores (GRSs). A high GRS (top 20-25% of the population) confers two to three times higher risk of PCa than average; a very high GRS (top 1-5%) confers six to eight times higher risk. GRSs are not specific for aggressive PCa, possibly due to methodological limitations and/or a field effect of an elevated risk for both low- and high-grade PCa. It is challenging to disentangle genetics from structural racism and social determinants of health to understand PCa racial disparities. GRSs are independently associated with a lethal PCa risk after accounting for family history and race/ancestry. Healthy lifestyle might partially mitigate the risk of lethal PCa.

CONCLUSIONS

Genetic risk assessment is becoming more common; implementation studies are needed to understand the implications and to avoid exacerbating healthcare disparities. Men with a high genetic risk of PCa can reasonably be encouraged to adhere to a healthy lifestyle.

PATIENT SUMMARY

Prostate cancer risk is inherited through rare mutations and through the combination of hundreds of common genetic markers. Some men with a high genetic risk (especially BRCA2 mutations) likely benefit from early screening for prostate cancer. The risk of lethal prostate cancer can be reduced through a healthy lifestyle.

Hypothesis-free phenotype prediction within a genetics-first framework

Cohort-wide sequencing studies have revealed that the largest category of variants is those deemed 'rare', even for the subset located in coding regions (99% of known coding variants are seen in less than 1% of the population. Associative methods give some understanding how rare genetic variants influence disease and organism-level phenotypes. But here we show that additional discoveries can be made through a knowledge-based approach using protein domains and ontologies (function and phenotype) that considers all coding variants regardless of allele frequency. We describe an ab initio, genetics-first method making molecular knowledge-based interpretations for exome-wide non-synonymous variants for phenotypes at the organism and cellular level. By using this reverse approach, we identify plausible genetic causes for developmental disorders that have eluded other established methods and present molecular hypotheses for the causal genetics of 40 phenotypes generated from a direct-to-consumer genotype cohort. This system offers a chance to extract further discovery from genetic data after standard tools have been applied.

Physiological changes and gene responses during Ganoderma lucidum growth with selenium supplementation

Ganoderma lucidum basidiomycota is highly appreciated for its health and nutrition value. In the present study, Ganoderma lucidum was cultivated as selenium transformation carrier, and the physiological changes and gene responses by selenium supplementation were revealed through high-throughput RNA-Seq technology. As a result, selenium supplementation increased the stipe length and the cap size, but decreased the cap thickness of G. lucidum. Mineral salt supplementation could greatly promote the formation of triterpene acids and selenium in G. lucidum. The highest yield was gained in the treatment with selenium content of 200 µg/g. Subsequently, the tissues of G. lucidum at budding and mature stages in this treatment group were sampled for transcriptome analysis and compared to those of a control group without selenium supplementation. A total of 16,113 expressed genes were obtained from the transcriptome of G. lucidum, and GO-annotated unigenes were mainly involved in molecular functions and KEGG-annotated ones were highly expressed in ribosomal pathway. Furthermore, genes involved in carbon metabolism pathway were most promoted by selenium at budding stage of G. lucidum, while gene expression was the highest in the pathway of amino acid biosynthesis at mature stage of G. lucidum. Specially, selenium-related genes in G. lucidum, such as GL23172-G, GL29881-G and GL28298-G, played a regulatory role in oxidoreductase, antioxidant activity and tryptophan synthesis. The results provide a theoretical basis for further study of selenium-enriched mushrooms and aid to development of Se-enriched foodstuff and health products made from fungi.

Array genotyping as diagnostic approach in medical genetics

Genotyping arrays are by far the most widely used genetic tests but are not generally utilized for diagnostic purposes in a medical context. In the present study, we examined the diagnostic value of a standard genotyping array (Illumina Global Screening Array) for a range of indications. Applications included stand-alone testing for specific variants (32 variants in 10 genes), first-tier array variant screening for monogenic conditions (10 different autosomal recessive metabolic diseases), and diagnostic workup for specific conditions caused by variants in multiple genes (suspected familial breast and ovarian cancer, and hypercholesterolemia). Our analyses showed a high analytical sensitivity and specificity of array-based analyses for validated and non-validated variants, and identified pitfalls that require attention. Ethical-legal assessment highlighted the need for a software solution that allows for individual indication-based consent and the reliable exclusion of non-consented results. Cost/time assessment revealed excellent performance of diagnostic array analyses, depending on indication, proband data, and array design. We have implemented some analyses in our diagnostic portfolio, but array optimization is required for the implementation of other indications.

Newborn Screening: Review of its Impact for Cystinosis

Newborn screening (NBS) programmes are considered to be one of the most successful secondary prevention measures in childhood to prevent or reduce morbidity and/or mortality via early disease identification and subsequent initiation of therapy. However, while many rare diseases can now be detected at an early stage using appropriate diagnostics, the introduction of a new target disease requires a detailed analysis of the entire screening process, including a robust scientific background, analytics, information technology, and logistics. In addition, ethics, financing, and the required medical measures need to be considered to allow the benefits of screening to be evaluated at a higher level than its potential harm. Infantile nephropathic cystinosis (INC) is a very rare lysosomal metabolic disorder. With the introduction of cysteamine therapy in the early 1980s and the possibility of renal replacement therapy in infancy, patients with cystinosis can now reach adulthood. Early diagnosis of cystinosis remains important as this enables initiation of cysteamine at the earliest opportunity to support renal and patient survival. Using molecular technologies, the feasibility of screening for cystinosis has been demonstrated in a pilot project. This review aims to provide insight into NBS and discuss its importance for nephropathic cystinosis using molecular technologies.