Impute.me: An Open-Source, Non-profit Tool for Using Data From Direct-to-Consumer Genetic Testing to Calculate and Interpret Polygenic Risk Scores

The Polygenic Score Catalog: new functionality and tools to enable FAIR research

Polygenic scores (PGS) have transformed human genetic research and have multiple potential clinical applications, including risk stratification for disease prevention and prediction of treatment response. Here, we present a series of recent enhancements to the PGS Catalog (www.PGSCatalog.org), the largest findable, accessible, interoperable, and reusable (FAIR) repository of PGS. These include expansions in data content and ancestral diversity as well as the addition of new features. We further present the PGS Catalog Calculator (pgsc_calc, https://github.com/PGScatalog/pgsc_calc), an open-source, scalable and portable pipeline to reproducibly calculate PGS that securely democratizes equitable PGS applications by implementing genetic ancestry estimation and score normalization using reference data. With the PGS Catalog & calculator users can now quantify an individual's genetic predisposition for hundreds of common diseases and clinically relevant traits. Taken together, these updates and tools facilitate the next generation of PGS, thus lowering barriers to the clinical studies necessary to identify where PGS may be integrated into clinical practice.

The ethics of polygenic scores in psychiatry: minefield or opportunity for patient-centered psychiatry?

Recent advancements in psychiatric genetics have sparked a lively debate on the opportunities and pitfalls of incorporating polygenic scores into clinical practice. Yet, several ethical concerns have been raised, casting doubt on whether further development and implementation of polygenic scores would be compatible with providing ethically responsible care. While these ethical issues warrant thoughtful consideration, it is equally important to recognize the unresolved need for guidance on heritability among patients and their families. Increasing the availability of genetic counseling services in psychiatry should be regarded as a first step toward meeting these needs. As a next step, future integration of novel genetic tools such as polygenic scores into genetic counseling may be a promising way to improve psychiatric counseling practice. By embedding the exploration of polygenic psychiatry into the supporting environment of genetic counseling, some of the previously identified ethical pitfalls may be prevented, and opportunities to bolster patient empowerment can be seized upon. To ensure an ethically responsible approach to psychiatric genetics, active collaboration with patients and their relatives is essential, accompanied by educational efforts to facilitate informed discussions between psychiatrists and patients.

A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools

Polygenetic Risk Scores are used to evaluate an individual's vulnerability to developing specific diseases or conditions based on their genetic composition, by taking into account numerous genetic variations. This article provides an overview of the concept of Polygenic Risk Scores (PRS). We elucidate the historical advancements of PRS, their advantages and shortcomings in comparison with other predictive methods, and discuss their conceptual limitations in light of the complexity of biological systems. Furthermore, we provide a survey of published tools for computing PRS and associated resources. The various tools and software packages are categorized based on their technical utility for users or prospective developers. Understanding the array of available tools and their limitations is crucial for accurately assessing and predicting disease risks, facilitating early interventions, and guiding personalized healthcare decisions. Additionally, we also identify potential new avenues for future bioinformatic analyzes and advancements related to PRS.

Taking the risk. A systematic review of ethical reasons and moral arguments in the clinical use of polygenic risk scores

Debates about the prospective clinical use of polygenic risk scores (PRS) have grown considerably in the last years. The potential benefits of PRS to improve patient care at individual and population levels have been extensively underlined. Nonetheless, the use of PRS in clinical contexts presents a number of unresolved ethical challenges and consequent normative gaps that hinder their optimal implementation. Here, we conducted a systematic review of reasons of the normative literature discussing ethical issues and moral arguments related to the use of PRS for the prevention and treatment of common complex diseases. In total, we have included and analyzed 34 records, spanning from 2013 to 2023. The findings have been organized in three major themes: in the first theme, we consider the potential harms of PRS to individuals and their kin. In the theme "Threats to health equity," we consider ethical concerns of social relevance, with a focus on justice issues. Finally, the theme "Towards best practices" collects a series of research priorities and provisional recommendations to be considered for an optimal clinical translation of PRS. We conclude that the use of PRS in clinical care reinvigorates old debates in matters of health justice; however, open questions, regarding best practices in clinical counseling, suggest that the ethical considerations applicable in monogenic settings will not be sufficient to face PRS emerging challenges.

Polygenic risk score comparator (PRScomp): Test population vs. worldwide populations

BACKGROUND

Polygenic risk scores (PRS) are a powerful tool for predicting an individual's genetic risk for complex diseases.

METHODS

We have developed a web service (PRScomp) as a user-friendly tool to evaluate PRS of the user own population and compare it with worldwide populations.

RESULTS

A disease/trait database has been constructed from GWAS Catalog summary statistics. Genotype data of test population is uploaded and merged with the reference dataset (1000 Genome Project and Human Genome Diversity Project) to obtain a file including the common SNPs. The user can select a disease/trait from the database and a curated set of risk markers is used to calculate summatory PRS. Distribution of z-scored PRS values is presented in publication-ready plots and text files that can be downloaded.

DISCUSSION

PRScomp can be useful for public health decision-making by identifying population-specific genetic risk factors and informing the development of targeted interventions for at-risk populations.

Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations

Polygenic risk scores (PRSs) have improved in predictive performance, but several challenges remain to be addressed before PRSs can be implemented in the clinic, including reduced predictive performance of PRSs in diverse populations, and the interpretation and communication of genetic results to both providers and patients. To address these challenges, the National Human Genome Research Institute-funded Electronic Medical Records and Genomics (eMERGE) Network has developed a framework and pipeline for return of a PRS-based genome-informed risk assessment to 25,000 diverse adults and children as part of a clinical study. From an initial list of 23 conditions, ten were selected for implementation based on PRS performance, medical actionability and potential clinical utility, including cardiometabolic diseases and cancer. Standardized metrics were considered in the selection process, with additional consideration given to strength of evidence in African and Hispanic populations. We then developed a pipeline for clinical PRS implementation (score transfer to a clinical laboratory, validation and verification of score performance), and used genetic ancestry to calibrate PRS mean and variance, utilizing genetically diverse data from 13,475 participants of the All of Us Research Program cohort to train and test model parameters. Finally, we created a framework for regulatory compliance and developed a PRS clinical report for return to providers and for inclusion in an additional genome-informed risk assessment. The initial experience from eMERGE can inform the approach needed to implement PRS-based testing in diverse clinical settings.

PRScalc, a privacy-preserving calculation of raw polygenic risk scores from direct-to-consumer genomics data

Motivation

Currently, the Polygenic Score (PGS) Catalog curates over 400 publications on over 500 traits corresponding to over 3000 polygenic risk scores (PRSs). To assess the feasibility of privately calculating the underlying multivariate relative risk for individuals with consumer genomics data, we developed an in-browserPRS calculator for genomic data that does not circulate any data or engage in any computation outside of the user's personal device.

Results

A prototype personal risk score calculator, created for research purposes, was developed to demonstrate how the PGS Catalog can be privately and readily applied to readily available direct-to-consumer genetic testing services, such as 23andMe. No software download, installation, or configuration is needed. The PRS web calculator matches individual PGS catalog entries with an individual's 23andMe genome data composed of 600k to 1.4 M single-nucleotide polymorphisms (SNPs). Beta coefficients provide researchers with a convenient assessment of risk associated with matched SNPs. This in-browser application was tested in a variety of personal devices, including smartphones, establishing the feasibility of privately calculating personal risk scores with up to a few thousand reference genetic variations and from the full 23andMe SNP data file (compressed or not).

Availability and implementation

The PRScalc web application is developed in JavaScript, HTML, and CSS and is available at GitHub repository (https://episphere.github.io/prs) under an MIT license. The datasets were derived from sources in the public domain: [PGS Catalog, Personal Genome Project].

How do experts in psychiatric genetics view the clinical utility of polygenic risk scores for schizophrenia?

Polygenic risk scores (PRS) are promising for identifying common variant-related inheritance for psychiatric conditions but their integration into clinical practice depends on their clinical utility and psychiatrists' understanding of PRS. Our online survey explored these issues with 276 professionals working in psychiatric genetics (RR: 19%). Overall, participants demonstrated knowledge of how to interpret PRS results. Their performance on knowledge-based questions was positively correlated with participants' self-reported familiarity with PRS (r = 0.21, p = 0.0006) although differences were not statistically significant (Wald Chi-square = 3.29, df = 1, p = 0.07). However, only 48.9% of all participants answered all knowledge questions correctly. Many participants (56.5%), especially researchers (42%), indicated having at least occasional conversations about the role of genetics in psychiatric conditions with patients and/or family members. Most participants (62.7%) indicated that PRS are not yet sufficiently robust for assessment of susceptibility to schizophrenia; most significant obstacles were low predictive power and lack of population diversity in available PRS (selected, respectively, by 53.6% and 29.3% of participants). Nevertheless, 89.8% of participants were optimistic about the use of PRS in the next 10 years, suggesting a belief that current shortcomings could be addressed. Our findings inform about the perceptions of psychiatric professionals regarding PRS and the application of PRS in psychiatry.

Australian parental perceptions of genomic newborn screening for non-communicable diseases

Background: Newborn bloodspot screening (NBS) programs have improved neonatal healthcare since the 1960s. Genomic sequencing now offers potential to generate polygenic risk score (PRS) that could be incorporated into NBS programs, shifting the focus from treatment to prevention of future noncommunicable disease (NCD). However, Australian parents' knowledge and attitudes regarding PRS for NBS is currently unknown. Methods: Parents with at least one Australian-born child under 18 years were invited via social media platforms to complete an online questionnaire aimed at examining parents' knowledge of NCDs, PRS, and precision medicine, their opinions on receiving PRS for their child, and considerations of early-intervention strategies to prevent the onset of disease. Results: Of 126 participants, 90.5% had heard the term "non-communicable disease or chronic condition," but only 31.8% and 34.4% were aware of the terms "polygenic risk score" and "precision medicine" respectively. A large proportion of participants said they would consider screening their newborn to receive a PRS for allergies (77.9%), asthma (81.0%), cancer (64.8%), cardiovascular disease (65.7%), mental illness (56.7%), obesity (49.5%), and type 2 diabetes (66.7%). Additionally, participants would primarily consider diet and exercise as interventions for specific NCDs. Discussion: The results from this study will inform future policy for genomic NBS, including expected rate of uptake and interventions that parents would consider employing to prevent the onset of disease.

Returning complex genetic risk information to promote better health-related behaviors: a commentary of the literature and suggested next steps

Genome-wide association studies aim to identify genetic variants that are associated with a disease phenotype in order to enhance precision medicine efforts. Despite the excitement surrounding the promise of precision medicine and interest among the public in accessing personalized genetic information, there has been little effort dedicated to understanding how complex genetic risk information could be incorporated into clinical practice to inform prevention, screening, and treatment. In this article, we briefly summarize the literature on the impact of receiving genetic risk information on health-related behavior, discuss the limitations of these studies, and outline the challenges that will need to be overcome, along with suggested next steps for future studies, to understand the true promise of precision medicine. The current literature demonstrates that there is no consistent or strong evidence that receiving complex genetic risk information, such as polygenic risk scores, has an impact on behavior; however, there are a number of limitations that may impact the failure to find significant effects associated with receiving genetic feedback. Behavior change is a complex process and simply providing genetic risk information without incorporating a theoretical perspective on behavior change diminishes the potential impact of receiving genetic risk information on actual behavior change. Future studies and interventions which return genetic feedback should be designed using theoretical frameworks of behavior change models to improve the impact of receiving personalized genetic information.

Revisiting informed consent in forensic genomics in light of current technologies and the times

Informed consent is based on basic ethical principles that should be considered when conducting biomedical and behavioral research involving human subjects. These principles-respect, beneficence, and justice-form the foundations of informed consent which in itself is grounded on three fundamental elements: information, comprehension, and voluntary participation. While informed consent has focused on human subjects and research, the practice has been adopted willingly in the forensic science arena primarily to acquire reference samples from family members to assist in identifying missing persons. With advances in molecular biology technologies, data mining, and access to metadata, it is important to assess whether the past informed consent process and in particular associated risks are concomitant with these increased capabilities. Given the state-of-the-art, areas in which informed consent may need to be modified and augmented are as follows: reference samples from family members in missing persons or unidentified human remains cases; targeted analysis of an individual(s) during forensic genetic genealogy cases to reduce an investigative burden; donors who provide their samples for validation studies (to include population studies and entry into databases that would be applied to forensic statistical calculations) to support implementation of procedures and operations of the forensic laboratory; family members that may contribute samples or obtain genetic information from a molecular autopsy; and use of medical and other acquired samples that could be informative for identification purposes. The informed consent process should cover (1) purpose for collection of samples; (2) process to analyze the samples (to include type of data); (3) benefits (to donor, target, family, community, etc. as applicable); (4) risks (to donor, target, family, community, etc. as applicable); (5) access to data/reports by the donor; (6) sample disposition; (7) removal of data process (i.e., expungement); (8) process to ask questions/assessment of comprehension; (9) follow-up processes; and (10) voluntary, signed, and dated consent. Issues surrounding these topics are discussed with an emphasis on addressing risk factors. Addressing informed consent will allow human subjects to make decisions voluntarily and with autonomy as well as secure the use of samples for intended use.

The Promise and Peril of Genetics

Human genetics is advancing at an unprecedented pace. Improvements in genotyping technology and rapidly falling costs have accelerated gene discovery. We can now comprehensively scan the genome, testing variation across millions of genetic markers, to identify specific variants associated with any outcome of interest. Large consortia consisting of hundreds of scientists are analyzing data from hundreds of thousands to millions of individuals. Multivariate methods now enable us to identify genes involved in underlying processes, to complement studies focused on specific disorders or traits. There has been an exponential increase in use of direct-to-consumer genetic feedback platforms. These advances are poised to have a widespread effect on medicine and society. However, with such rapid progress will come ethical, social, and legal challenges. Among those challenges is the need for increased efforts to enhance public understanding of the ways genes contribute to complex behavioral outcomes, and for increased diversity in the field of genetics to ensure that all people benefit from advances. Psychologists can play an important role in addressing the inevitable questions that will arise as genetics increasingly becomes mainstream.

A comprehensive evaluation of polygenic score and genotype imputation performances of human SNP arrays in diverse populations

Regardless of the overwhelming use of next-generation sequencing technologies, microarray-based genotyping combined with the imputation of untyped variants remains a cost-effective means to interrogate genetic variations across the human genome. This technology is widely used in genome-wide association studies (GWAS) at bio-bank scales, and more recently, in polygenic score (PGS) analysis to predict and stratify disease risk. Over the last decade, human genotyping arrays have undergone a tremendous growth in both number and content making a comprehensive evaluation of their performances became more important. Here, we performed a comprehensive performance assessment for 23 available human genotyping arrays in 6 ancestry groups using diverse public and in-house datasets. The analyses focus on performance estimation of derived imputation (in terms of accuracy and coverage) and PGS (in terms of concordance to PGS estimated from whole-genome sequencing data) in three different traits and diseases. We found that the arrays with a higher number of SNPs are not necessarily the ones with higher imputation performance, but the arrays that are well-optimized for the targeted population could provide very good imputation performance. In addition, PGS estimated by imputed SNP array data is highly correlated to PGS estimated by whole-genome sequencing data in most cases. When optimal arrays are used, the correlations of PGS between two types of data are higher than 0.97, but interestingly, arrays with high density can result in lower PGS performance. Our results suggest the importance of properly selecting a suitable genotyping array for PGS applications. Finally, we developed a web tool that provides interactive analyses of tag SNP contents and imputation performance based on population and genomic regions of interest. This study would act as a practical guide for researchers to design their genotyping arrays-based studies. The tool is available at: https://genome.vinbigdata.org/tools/saa/ .

Psychiatric polygenic risk scores: Child and adolescent psychiatrists' knowledge, attitudes, and experiences

Psychiatric polygenic risk scores (PRS) have potential utility in psychiatric care and prevention, but there are concerns about their implementation. We surveyed 960 US-based practicing child and adolescent psychiatrists' (CAP) about their experiences, perspectives, and potential uses of psychiatric PRS. While 23% of CAP reported that they had never heard of PRS, 10 % of respondents have had a patient/family bring PRS to them and 4% have generated PRS for patients. Though 25% stated they would request PRS if a patient/caregiver asked, 35% indicated that nothing would prompt them to request PRS. Most respondents (54%) believed psychiatric PRS are currently at least slightly useful and 87% believed they will be so in 5 years. More than 70% indicated they would take action in response to a child with a top fifth percentile psychiatric PRS but no diagnosis: 48% would increase monitoring of symptoms, 42% would evaluate for current symptoms, and 4% would prescribe medications. Yet, most respondents were concerned that high-PRS results could lead to overtreatment and negatively impact patients' emotional well-being. Findings indicate emerging use of psychiatric PRS within child and adolescent psychiatry in the US. It is critical to examine the ethical and clinical challenges that PRS may generate and begin efforts to promote their informed and responsible use.

The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.

Polygenic scores in biomedical research

Public health strategies aimed at disease prevention or early detection and intervention have the potential to advance human health worldwide. However, their success depends on the identification of risk factors that underlie disease burden in the general population. Genome-wide association studies (GWAS) have implicated thousands of single-nucleotide polymorphisms (SNPs) in common complex diseases or traits. By calculating a weighted sum of the number of trait-associated alleles harboured by an individual, a polygenic score (PGS), also called a polygenic risk score (PRS), can be constructed that reflects an individual’s estimated genetic predisposition for a given phenotype. Here, we ask six experts to give their opinions on the utility of these probabilistic tools, their strengths and limitations, and the remaining barriers that need to be overcome for their equitable use.

Genetically influenced externalizing and internalizing risk pathways as novel prevention targets

Objective: Risky substance use among college students is widespread, and associated with numerous adverse consequences. Current interventions focus primarily on students' current substance use; we hypothesize that shifting focus from current use to underlying risk factors is a complementary approach that may improve effectiveness of prevention/intervention programming. This approach aligns with the personalized medicine movement, which aims to harness knowledge about underlying etiological factors to provide individuals with specific information about their unique risk profiles and personalized recommendations, to motivate and enable individuals to better self-regulate their health. Method: Our group is building and evaluating an online Personalized Feedback Program (PFP) for college students that provides feedback about the individual's underlying genetically influenced externalizing and internalizing risk factors for substance use, along with personalized recommendations/resources. The project capitalizes on work from a university-wide research project (Spit for Science; S4S), in which > 12,000 students (˜70% of 5 years of incoming freshmen) are being followed longitudinally to assess substance use and related factors across the college years. In this article, we describe our foundational work to develop the PFP. Results: From the S4S data, we have identified risk factors across four domains (Sensation Seeking, Impulsivity, Extraversion, and Neuroticism) that are correlated with college students' substance use. We developed an online self-guided PFP, in collaboration with professionals from student affairs, and using feedback from students, with the ultimate goal of conducting a randomized clinical trial. Conclusion: The provision of personalized risk information represents a novel approach to complement and extend existing college substance use programming. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Challenges and Opportunities for Developing More Generalizable Polygenic Risk Scores

Polygenic risk scores (PRS) estimate an individual's genetic likelihood of complex traits and diseases by aggregating information across multiple genetic variants identified from genome-wide association studies. PRS can predict a broad spectrum of diseases and have therefore been widely used in research settings. Some work has investigated their potential applications as biomarkers in preventative medicine, but significant work is still needed to definitively establish and communicate absolute risk to patients for genetic and modifiable risk factors across demographic groups. However, the biggest limitation of PRS currently is that they show poor generalizability across diverse ancestries and cohorts. Major efforts are underway through methodological development and data generation initiatives to improve their generalizability. This review aims to comprehensively discuss current progress on the development of PRS, the factors that affect their generalizability, and promising areas for improving their accuracy, portability, and implementation.

Novel functional genomics approaches bridging neuroscience and psychiatry

The possibility of establishing a metric of individual genetic risk for a particular disease or trait has sparked the interest of the clinical and research communities, with many groups developing and validating genomic profiling methodologies for their potential application in clinical care. Current approaches for calculating genetic risk to specific psychiatric conditions consist of aggregating genome-wide association studies-derived estimates into polygenic risk scores, which broadly represent the number of inherited risk alleles for an individual. While the traditional approach for polygenic risk score calculation aggregates estimates of gene-disease associations, novel alternative approaches have started to consider functional molecular phenotypes that are closer to genetic variation and are less penalized by the multiple testing required in genome-wide association studies. Moving the focus from genotype-disease to genotype-gene regulation frameworks, these novel approaches incorporate prior knowledge regarding biological processes involved in disease and aggregate estimates for the association of genotypes and phenotypes using multi-omics data modalities. In this review, we discuss and list different functional genomics tools that can be used and integrated to inform researchers and clinicians for a better understanding and diagnosis of psychopathology. We suggest that these novel approaches can help generate biologically driven hypotheses for polygenic signals that can ultimately serve the clinical community as potential biomarkers of psychiatric disease susceptibility.

Inherited genetics of adult diffuse glioma and polygenic risk scores-a review

Knowledge about inherited and acquired genetics of adult diffuse glioma has expanded significantly over the past decade. Genomewide association studies (GWAS) stratified by histologic subtype identified six germline variants that were associated specifically with glioblastoma (GBM) and 12 that were associated with lower grade glioma. A GWAS performed using the 2016 WHO criteria, stratifying patients by IDH mutation and 1p/19q codeletion (as well as TERT promoter mutation), discovered that many of the known variants are associated with specific WHO glioma subtypes. In addition, the GWAS stratified by molecular group identified two additional novel regions: variants in D2HGDH that were associated with tumors that had an IDH mutation and a variant near FAM20C that was associated with tumors that had both IDH mutation and 1p/19q codeletion. The results of these germline associations have been used to calculate polygenic risk scores, from which to estimate relative and absolute risk of overall glioma and risk of specific glioma subtypes. We will review the concept of polygenic risk models and their potential clinical utility, as well as discuss the published adult diffuse glioma polygenic risk models. To date, these prior genetic studies have been done on European populations. Using the published glioma polygenic risk model, we show that the genetic associations published to date do not generalize across genetic ancestries, demonstrating that genetic studies need to be done on more diverse populations.

Applications of Machine Learning Models to Predict and Prevent Obesity: A Mini-Review

Research on obesity and related diseases has received attention from government policymakers; interventions targeting nutrient intake, dietary patterns, and physical activity are deployed globally. An urgent issue now is how can we improve the efficiency of obesity research or obesity interventions. Currently, machine learning (ML) methods have been widely applied in obesity-related studies to detect obesity disease biomarkers or discover intervention strategies to optimize weight loss results. In addition, an open source of these algorithms is necessary to check the reproducibility of the research results. Furthermore, appropriate applications of these algorithms could greatly improve the efficiency of similar studies by other researchers. Here, we proposed a mini-review of several open-source ML algorithms, platforms, or related databases that are of particular interest or can be applied in the field of obesity research. We focus our topic on nutrition, environment and social factor, genetics or genomics, and microbiome-adopting ML algorithms.

Genetics in psychiatry: Methods, clinical applications and future perspectives

Psychiatric disorders and related traits have a demonstrated genetic component, with heritability estimated by twin studies generally between 80% and 40%. Their pathogenesis is complex and multi-determined: environmental factors interact with a polygenic architecture, making difficult the development of models able to stratify patients or predict mental health outcomes. Despite this difficult challenge, relevant progress has been made in the field of psychiatric genetics in recent years. This review aims to present the main current methods in psychiatric genetics, their output, limitations, clinical applications, and possible future developments. Genome-wide association studies (GWASs) performed in increasingly large samples have led to the identification of replicated genetic loci associated with the risk of major psychiatric disorders, including schizophrenia and mood disorders. Statistical and biological approaches have been developed to improve our understanding of the etiopathogenetic mechanisms behind genome-wide significant associations, as well as for estimating the cumulative effect of risk variants at the individual level and the genetic overlap between different disorders, as pleiotropy is the rule rather than the exception. Clinical applications are available in the pharmacogenetics field. The main issues that remain to be addressed include improving ethnic diversity in genetic studies and the optimization of statistical power through methodological improvements, such as the definition of dimensional phenotypes with specific biological correlates and the integration of different types of omics data.

Genetic testing-whether to allow complete freedom? Direct to consumer tests versus genetic tests for medical purposes

Direct-to-consumer tests opened the opportunity of genetic testing without medical supervision, e.g., without medical referral and medical interpretation of the results. Thus, these approaches allow for free access to information concerning individual genetic profile increasing the area of personal freedom, but also posing the risk of false (positive and negative) or misinterpreted results along with health and psychological negative consequences. The paper discusses medical and non-medical applications of DTC, exploring also the legal framework implemented by European states and organizations. These legal acts strive to control the developing DTC market through such basic principles as patient protection, informed consent, medical information confidentiality, and the rights to know and to refuse knowledge about one's genetic predispositions.

Why do people seek out polygenic risk scores for complex disorders, and how do they understand and react to results?

We sought to explore individuals' motivations for using their direct-to-consumer genetic testing data to generate polygenic risk scores (PRSs) using a not-for-profit third-party tool, and to assess understanding of, and reaction to their results. Using a cross-sectional design, users of Impute.me who had already accessed PRS results were invited to complete an online questionnaire asking about demographics, motivations for seeking PRSs, understanding and interpretation of PRSs, and two validated scales regarding reactions to results-the Impact of Event Scale Revised (IES-R) and the Feelings About genomiC Testing Results (FACToR). Independent samples T-tests and ANOVA were used to explore associations between the variables. 227 individuals participated in the study. The most frequently reported motivation was general curiosity (98.2%). Only 25.6% of participants correctly answered all questions assessing understanding/interpretation of PRSs. Over half of participants (60.8%) experienced a negative reaction (upset, anxious, and/or sad on FACToR scale) after receiving their PRSs and 5.3% scored over the threshold for potential post-traumatic stress disorder on the IES-R. Lower understanding about PRS was associated with experiencing a negative psychological reaction (P values <0.001). Higher quality pre-test information, particularly to improve understanding, and manage expectations for PRS may be useful in limiting negative psychological reactions.

Evaluating the impact of a new educational tool on understanding of polygenic risk scores for alcohol use disorder

INTRODUCTION

As gene identification efforts have advanced in psychiatry, so have aspirations to use genome-wide polygenic information for prevention and intervention. Although polygenic risk scores (PRS) for substance use and psychiatric outcomes are not yet available in clinical settings, individuals can access their PRS through online direct-to-consumer resources. One of these widely used websites reports that alcohol use disorder is the third most requested PRS out of >1,000 conditions. However, data indicate that there are misunderstandings about complex genetic concepts, with a lower understanding of PRS being associated with a more negative impact of receiving polygenic risk information. There is a need to develop and evaluate educational tools to increase understanding of PRS.

METHODS

We conducted a randomized controlled trial to evaluate the impact of web-based educational information on understanding of PRS for alcohol use disorder. A total of 325 college students (70.4% female; 43.6% White; mean age = 18.9 years) from an urban, diverse university completed the study.

RESULTS

Overall, participants were highly satisfied with the educational information. Results from a one-way ANOVA indicated that there was a significant increase in overall understanding of PRS for alcohol use disorder (p-value < 0.001), among individuals who received educational information about PRS and alcohol use disorder, as compared to receiving no accompanying information (adj. p-value < 0.001), or educational information about alcohol use disorder only (adj. p-value < 0.001).

DISCUSSION

These findings suggest that the web-based educational tool could be provided alongside polygenic risk information in order to enhance understanding and interpretation of the information.

CLINICAL TRIAL REGISTRATION

[ClinicalTrials.gov], identifier [NCT05143073].

Pharmacogenetics of Addiction Therapy

Drug addiction is a serious relapsing disease that has high costs to society and to the individual addicts. Treatment of these addictions is still in its nascency, with only a few examples of successful therapies. Therapeutic response depends upon genetic, biological, social, and environmental components. A role for genetic makeup in the response to treatment has been shown for several addiction pharmacotherapies with response to treatment based on individual genetic makeup. In this chapter, we will discuss the role of genetics in pharmacotherapies, specifically for cocaine, alcohol, and opioid dependences. The continued elucidation of the role of genetics should aid in the development of new treatments and increase the efficacy of existing treatments.

Polygenic risk scores: An overview from bench to bedside for personalised medicine

Since the first polygenic risk score (PRS) in 2007, research in this area has progressed significantly. The increasing number of SNPs that have been identified by large scale GWAS analyses has fuelled the development of a myriad of PRSs for a wide variety of diseases and, more recently, to PRSs that potentially identify differential response to specific drugs. PRSs constitute a composite genomic biomarker and potential applications for PRSs in clinical practice encompass risk prediction and disease screening, early diagnosis, prognostication, and drug stratification to improve efficacy or reduce adverse drug reactions. Nevertheless, to our knowledge, no PRSs have yet been adopted into routine clinical practice. Beyond the technical considerations of PRS development, the major challenges that face PRSs include demonstrating clinical utility and circumnavigating the implementation of novel genomic technologies at scale into stretched healthcare systems. In this review, we discuss progress in developing disease susceptibility PRSs across multiple medical specialties, development of pharmacogenomic PRSs, and future directions for the field.

PAGEANT: personal access to genome and analysis of natural traits

GWASs have identified numerous genetic variants associated with a wide variety of diseases, yet despite the wide availability of genetic testing the insights that would enhance the interpretability of these results are not widely available to members of the public. As a proof of concept and demonstration of technological feasibility, we developed PAGEANT (Personal Access to Genome & Analysis of Natural Traits), usable through Graphical User Interface or command line-based version, aiming to serve as a protocol and prototype that guides the overarching design of genetic reporting tools. PAGEANT is structured across five core modules, summarized by five Qs: (i) quality assurance of the genetic data; (ii) qualitative assessment of genetic characteristics; (iii) quantitative assessment of health risk susceptibility based on polygenic risk scores and population reference; (iv) query of third-party variant databases (e.g. ClinVAR and PharmGKB) and (v) quick Response code of genetic variants of interest. Literature review was conducted to compare PAGEANT with academic and industry tools. For 2504 genomes made publicly available through the 1000 Genomes Project, we derived their genomic characteristics for a suite of qualitative and quantitative traits. One exemplary trait is susceptibility to COVID-19, based on the most up-to-date scientific findings reported.

A Web Portal for Communicating Polygenic Risk Score Results for Health Care Use-The P5 Study

We present a method for communicating personalized genetic risk information to citizens and their physicians using a secure web portal. We apply the method for 3,177 Finnish individuals in the P5 Study where estimates of genetic and absolute risk, based on genetic and clinical risk factors, of future disease are reported to study participants, allowing individuals to participate in managing their own health. Our method facilitates using polygenic risk score as a personalized tool to estimate a person's future disease risk while offering a way for health care professionals to utilize the polygenic risk scores as a preventive tool in patient care.

A systematic review of gene-by-intervention studies of alcohol and other substance use

Alcohol and other substance use problems are common, and the efficacy of current prevention and intervention programs is limited. Genetics may contribute to differential effectiveness of psychosocial prevention and intervention programs. This paper reviews gene-by-intervention (G×I) studies of alcohol and other substance use, and implications for integrating genetics into prevention science. Systematic review yielded 17 studies for inclusion. Most studies focused on youth substance prevention, alcohol was the most common outcome, and measures of genotype were heterogeneous. All studies reported at least one significant G×I interaction. We discuss these findings in the context of the history and current state of genetics, and provide recommendations for future G×I research. These include the integration of genome-wide polygenic scores into prevention studies, broad outcome measurement, recruitment of underrepresented populations, testing mediators of G×I effects, and addressing ethical implications. Integrating genetic research into prevention science, and training researchers to work fluidly across these fields, will enhance our ability to determine the best intervention for each individual across development. With growing public interest in obtaining personalized genetic information, we anticipate that the integration of genetics and prevention science will become increasingly important as we move into the era of precision medicine.

Design and user experience testing of a polygenic score report: a qualitative study of prospective users

Background

Polygenic scores—which quantify inherited risk by integrating information from many common sites of DNA variation—may enable a tailored approach to clinical medicine. However, alongside considerable enthusiasm, we and others have highlighted a lack of standardized approaches for score disclosure. Here, we review the landscape of polygenic score reporting and describe a generalizable approach for development of a polygenic score disclosure tool for coronary artery disease.

Methods

We assembled a working group of clinicians, geneticists, data visualization specialists, and software developers. The group reviewed existing polygenic score reports and then designed a two-page mock report for coronary artery disease. We then conducted a qualitative user-experience study with this report using an interview guide focused on comprehension, experience, and attitudes. Interviews were transcribed and analyzed for themes identification to inform report revision.

Results

Review of nine existing polygenic score reports from commercial and academic groups demonstrated significant heterogeneity, reinforcing the need for additional efforts to study and standardize score disclosure. Using a newly developed mock score report, we conducted interviews with ten adult individuals (50% females, 70% without prior genetic testing experience, age range 20–70 years) recruited via an online platform. We identified three themes from interviews: (1) visual elements, such as color and simple graphics, enable participants to interpret, relate to, and contextualize their polygenic score, (2) word-based descriptions of risk and polygenic scores presented as percentiles were the best recognized and understood, (3) participants had varying levels of interest in understanding complex genomic information and therefore would benefit from additional resources that can adapt to their individual needs in real time. In response to user feedback, colors used for communicating risk were modified to minimize unintended color associations and odds ratios were removed. All 10 participants expressed interest in receiving a polygenic score report based on their personal genomic information.

Conclusions

Our findings describe a generalizable approach to develop a polygenic score report understandable by potential patients. Although additional studies are needed across a wider spectrum of patient populations, these results are likely to inform ongoing efforts related to polygenic score disclosure within clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01056-0.

Investigating perceived heritability of mental health disorders and attitudes toward genetic testing in the United States, United Kingdom, and Australia

Our beliefs about the heritability of psychiatric traits may influence how we respond to the use of genetic information in this area. In the present study, we aim to inform future education campaigns as well as genetic counseling interventions by exploring common fears and misunderstandings associated with learning about genetic predispositions for mental health disorders. We surveyed 3,646 genetic research participants from Australia, and 960 members of the public from the United Kingdom, and the United States, and evaluated attitudes toward psychiatric genetic testing. Participants were asked hypothetical questions about their interest in psychiatric genetic testing, perceived usefulness of psychiatric genetic testing, and beliefs about malleability of behavior, among others. We also asked them to estimate the heritability of alcohol dependence, schizophrenia, and major depression. We found a high interest in psychiatric genetic testing. In most cases, more than a third of the participants showed serious concerns related to learning about personal genetic predisposition, such as not wanting to have children if they knew they had a high genetic predisposition, or not wanting to choose a partner with a high genetic predisposition for a mental health problem. Finally, we found a significant association between most participants' attitudes and their lay estimates of heritability, which highlights the complexity of educating the public about genetics.

A comparison of genotyping arrays

Array technology to genotype single-nucleotide variants (SNVs) is widely used in genome-wide association studies (GWAS), clinical diagnostics, and linkage studies. Arrays have undergone a tremendous growth in both number and content over recent years making a comprehensive comparison all the more important. We have compared 28 genotyping arrays on their overall content, genome-wide coverage, imputation quality, presence of known GWAS loci, mtDNA variants and clinically relevant genes (i.e., American College of Medical Genetics (ACMG) actionable genes, pharmacogenetic genes, human leukocyte antigen (HLA) genes and SNV density). Our comparison shows that genome-wide coverage is highly correlated with the number of SNVs on the array but does not correlate with imputation quality, which is the main determinant of GWAS usability. Average imputation quality for all tested arrays was similar for European and African populations, indicating that this is not a good criterion for choosing a genotyping array. Rather, the additional content on the array, such as pharmacogenetics or HLA variants, should be the deciding factor. As the research question of a study will in large part determine which class of genes are of interest, there is not just one perfect array for all different research questions. This study can thus help as a guideline to determine which array best suits a study's requirements.

Evaluation of polygenic prediction methodology within a reference-standardized framework

The predictive utility of polygenic scores is increasing, and many polygenic scoring methods are available, but it is unclear which method performs best. This study evaluates the predictive utility of polygenic scoring methods within a reference-standardized framework, which uses a common set of variants and reference-based estimates of linkage disequilibrium and allele frequencies to construct scores. Eight polygenic score methods were tested: p-value thresholding and clumping (pT+clump), SBLUP, lassosum, LDpred1, LDpred2, PRScs, DBSLMM and SBayesR, evaluating their performance to predict outcomes in UK Biobank and the Twins Early Development Study (TEDS). Strategies to identify optimal p-value thresholds and shrinkage parameters were compared, including 10-fold cross validation, pseudovalidation and infinitesimal models (with no validation sample), and multi-polygenic score elastic net models. LDpred2, lassosum and PRScs performed strongly using 10-fold cross-validation to identify the most predictive p-value threshold or shrinkage parameter, giving a relative improvement of 16-18% over pT+clump in the correlation between observed and predicted outcome values. Using pseudovalidation, the best methods were PRScs, DBSLMM and SBayesR. PRScs pseudovalidation was only 3% worse than the best polygenic score identified by 10-fold cross validation. Elastic net models containing polygenic scores based on a range of parameters consistently improved prediction over any single polygenic score. Within a reference-standardized framework, the best polygenic prediction was achieved using LDpred2, lassosum and PRScs, modeling multiple polygenic scores derived using multiple parameters. This study will help researchers performing polygenic score studies to select the most powerful and predictive analysis methods.

Interest in Genetic Feedback for Alcohol Use Disorder and Related Substance Use and Psychiatric Outcomes among Young Adults

An exponential growing number of individuals are accessing genetic risk information via direct to consumer companies. Alcohol dependence is the third most accessed genetic risk score on a publicly available direct to consumer website. Better understanding of the degree to which individuals are interested in receiving personalized genetic feedback, the factors that relate to interest, and genetic knowledge will be critical to lay the foundation for precision medicine initiatives, especially for substance use and psychiatric outcomes, where less is known. To assess interest in receiving genetic feedback for alcohol use disorder (AUD) and understanding of genetic concepts related to psychiatric conditions, we conducted a survey with participants recruited from a registry that enrolled incoming cohorts of freshmen at an urban public university; 205 participants (76.5% female; 58.9% self-reported as White; Mage = 24.48 years) completed the survey. Results indicated that participants are highly interested in receiving genetic feedback for AUD (79.0%) but there is a lack of understanding of complex genetic concepts in a sizable proportion of the sample (25.4%). Additional research is needed to assess how to address this lack of knowledge before genetic feedback for AUD can be returned in a way that benefits the individual.

How to Utilize Clinical and Genetic Information for Personalized Treatment of Major Depressive Disorder: Step by Step Strategic Approach

Depression is the single largest contributor to non-fatal health loss and affects 322 million people globally. The clinical heterogeneity of this disorder shows biological correlates and it makes the personalization of antidepressant prescription an important pillar of treatment. There is increasing evidence of genetic overlap between depression, other psychiatric and non-psychiatric disorders, which varies across depression subtypes. Therefore, the first step of clinical evaluation should include a careful assessment of psychopathology and physical health, not limited to previously diagnosed disorders. In part of the patients indeed the pathogenesis of depression may be strictly linked to inflammatory and metabolic abnormalities, and the treatment should target these as much as the depressive symptoms themselves. When the evaluation of the symptom and drug tolerability profile, the concomitant biochemical abnormalities and physical conditions is not enough and at least one pharmacotherapy failed, the genotyping of variants in CYP2D6/CYP2C19 (cytochromes responsible for antidepressant metabolism) should be considered. Individuals with altered metabolism through one of these enzymes may benefit from some antidepressants rather than others or need dose adjustments. Finally, if available, the polygenic predisposition towards cardio-metabolic disorders can be integrated with non-genetic risk factors to tune the identification of patients who should avoid medications associated with this type of side effects. A sufficient knowledge of the polygenic risk of complex medical and psychiatric conditions is becoming relevant as this information can be obtained through direct-to-consumer genetic tests and in the future it may provided by national health care systems.

Genetic feedback for psychiatric conditions: Where are we now and where are we going

Genome-wide association studies are rapidly advancing our understanding of the genetic architecture of complex disorders, including many psychiatric conditions such as major depression, schizophrenia, and substance use disorders. One common goal of genome-wide association studies is to use findings for enhanced clinical prediction in the future, which can aid in identifying at-risk individuals to enable more effective prevention screening and treatment strategies. In order to achieve this goal, we first need to gain a better understanding of the issues surrounding the return of complex genetic results. In this article, we summarize the current literature on: (a) genetic literacy in the general population, (b) the public's interest in receiving genetic test results for psychiatric conditions, (c) how individuals react to and interpret their genotypic information for specific psychiatric conditions, and (d) gaps in our knowledge that will be critical to address as we move toward returning genotypic information for psychiatric conditions in both research and clinical settings. By reviewing extant studies, we aim to increase awareness of the potential benefits and consequences of returning genotypic information for psychiatric conditions.