Editorial: Methods in applied genetic epidemiology 2022

BackgroundAlzheimer’s disease, among other neurodegenerative disorders, spans decades in individuals’ life and exhibits complex progression, symptoms and pathophysiology. Early diagnosis is essential for disease prevention and therapeutic intervention. Genetics may help identify individuals at high risk. As thousands of genetic variants may contribute to the genetic risk of Alzheimer’s disease, the polygenic risk score (PRS) approach has been shown to be useful for disease risk prediction. The APOE-ε4 allele is a known common variant associated with high risk to AD, but also associated with earlier onset. Rare variants usually have higher effect sizes than common ones; their impact may not be well captured by the PRS. Instead of standardised PRS, we propose to calculate the disease probability as a measure of disease risk that allows comparison between individuals.MethodsWe estimate AD risk as a probability based on PRS and separately accounting for APOE, AD rare variants and the disease prevalence in age groups. The mathematical framework makes use of genetic variants effect sizes from summary statistics and AD disease prevalence in age groups.ResultsThe AD probability varies with respect to age, APOE status and presence of rare variants. In age group 65+, the probability of AD grows from 0.03 to 0.18 (without APOE) and 0.07 to 0.7 (APOE e4e4 carriers) as PRS increases. In 85+, these values are 0.08–0.6 and 0.3–0.85. Presence of rare mutations, e.g. in TREM2, may increase the probability (in 65+) from 0.02 at the negative tail of the PRS to 0.3.ConclusionsOur approach accounts for the varying disease prevalence in different genotype and age groups when modelling the APOE and rare genetic variants risk in addition to PRS. This approach has potential for use in a clinical setting and can easily be updated for novel rare variants and for other populations or confounding factors when appropriate genome-wide association data become available.

Background: Genome-wide association studies (GWASs) have enhanced our understanding of the genetic basis of coronary artery disease (CAD), and polygenic risk scores (PRSs) have facilitated the assessment of genetic risk. However, these methods predominantly focus on common variants due to statistical power, potentially leaving rare variants insufficiently analyzed and thus limiting the predictive performance of PRS. Methods: We conducted whole genome sequencing (WGS) of 1,752 Japanese early-onset myocardial infarction (MI) patients and 3,019 controls from Biobank Japan (BBJ). We performed case-control association studies including GWAS and gene-based tests, as well as a novel machine learning-based framework. In this framework, we developed a penalized regression model to predict the CAD status from genome-wide rare nonsynonymous variants. The model identified the minimal set of most distinguishing features (genes) and generated a rare variant-based risk score (RVS). The RVS was evaluated on an independent validation WGS cohort of 200 cases and 824 controls. We also derived a PRS based on CAD-GWAS (25,668 CAD cases vs 141,667 controls from BBJ) to compare the properties and performance between the RVS and PRS. Results: In the case-control studies, only two common variants in chromosome 12 were identified in GWAS, with no genes in gene-based analysis (SKAT-O), suggesting the challenges in rare variant analysis. On the other hand, our machine-learning framework identified 59 CAD-related genes, including LDLR, a causal gene of familial hypercholesteremia. Functional analyses revealed that various biological pathways, including lipid metabolism, immune system, and vessel development, are involved in CAD. For the genetic risk prediction, RVS significantly predicted CAD (area under the curve [AUC], 0.58; p=0.001, pseudo-R2, 0.051; p=7.92*10-9). RVS was significantly associated with LDL cholesterol levels and coagulation function (Pearson’s r, 0.21; p=4.5*10-5 and 0.10; p=0.03, respectively) and MI patients with high RVS (top 5%) showed higher cardiovascular mortality rate (p=0.03, log-rank test), highlighting the clinical importance of RVS. Finally, the combined risk score (CRS) of RVS and PRS significantly improved CAD prediction compared to PRS (AUC, 0.66 (CRS) vs 0.61 (PRS); p=0.007, pseudo-R2, 0.093 (CRS) vs 0.040 (PRS); p=0.0018, Figure). Conclusions: Our machine learning framework successfully characterized rare variants and enhanced genetic risk prediction in CAD.

Exploring the role of low-frequency and rare exonic variants in alcohol and tobacco use

Rare sequence variation in genes underlying cardiac repolarization and common polygenic variation influence QT interval duration. However, current clinical genetic testing of individuals with unexplained QT prolongation is restricted to examination of monogenic rare variants. The recent emergence of large-scale biorepositories with sequence data enables examination of the joint contribution of rare and common variations to the QT interval in the population. We performed a genome-wide association study of the QTc in 84 630 UK Biobank participants and created a polygenic risk score (PRS). Among 26 976 participants with whole-genome sequencing and ECG data in the TOPMed (Trans-Omics for Precision Medicine) program, we identified 160 carriers of putative pathogenic rare variants in 10 genes known to be associated with the QT interval. We examined QTc associations with the PRS and with rare variants in TOPMed. Fifty-four independent loci were identified by genome-wide association study in the UK Biobank. Twenty-one loci were novel, of which 12 were replicated in TOPMed. The PRS composed of 1 110 494 common variants was significantly associated with the QTc in TOPMed (ΔQTc/decile of PRS=1.4 ms [95% CI, 1.3 to 1.5]; P=1.1×10-196). Carriers of putative pathogenic rare variants had longer QTc than noncarriers (ΔQTc=10.9 ms [95% CI, 7.4 to 14.4]). Of individuals with QTc>480 ms, 23.7% carried either a monogenic rare variant or had a PRS in the top decile (3.4% monogenic, 21% top decile of PRS). QTc duration in the population is influenced by both rare variants in genes underlying cardiac repolarization and polygenic risk, with a sizeable contribution from polygenic risk. Comprehensive assessment of the genetic determinants of QTc prolongation includes incorporation of both polygenic and monogenic risk.

Rare-variant and polygenic analyses of amyotrophic lateral sclerosis in the French-Canadian genome

Challenges With Colorectal Cancer Family History Assessment—Motivation to Translate Polygenic Risk Scores Into Practice

Genetics play an important role in systemic lupus erythematosus (SLE) pathogenesis. We calculated the prevalence of rare variants in known monogenic lupus genes among children suspected of monogenic lupus. We completed paired-end genome-wide sequencing (whole genome sequencing [WGS] or whole exome sequencing) in patients suspected of monogenic lupus, and focused on 36 monogenic lupus genes. We prioritized rare (minor allele frequency < 1%) exonic, nonsynonymous, and splice variants with predicted pathogenicity classified as deleterious variants (Combined Annotation Dependent Depletion [CADD], PolyPhen2, and Sorting Intolerant From Tolerant [SIFT] scores). Additional filtering restricted to predicted damaging variants by considering reported zygosity. In those with WGS (n = 69), we examined copy number variants (CNVs) > 1 kb in size. We created additive non-HLA and HLA SLE genetic risk scores (GRSs) using common SLE-risk single-nucleotide polymorphisms. We tested the relationship between SLE GRSs and the number of rare variants with multivariate logistic models, adjusted for sex, ancestry, and age of diagnosis. The cohort included 71 patients, 80% female, with a mean age at diagnosis of 8.9 (SD 3.2) years. We identified predicted damaging variants in 9 (13%) patients who were significantly younger at diagnosis compared to those without a predicted damaging variant (6.8 [SD 2.1] years vs 9.2 [SD 3.2] years, P = 0.01). We did not identify damaging CNVs. There was no significant association between non-HLA or HLA SLE GRSs and the odds of carrying ≥ 1 rare variant in multivariate analyses. In a cohort of patients with suspected monogenic lupus who underwent genome-wide sequencing, 13% carried rare predicted damaging variants for monogenic lupus. Additional studies are needed to validate our findings.

Background: Early-onset atrial fibrillation (AF) exhibits distinct clinical and genetic profiles compared to AF in older adults. The increasing detection of AF among younger patients—often in the absence of traditional risk factors—has raised interest in the genetic determinants underlying the condition. This review aims to synthesize current evidence on the genetic architecture of early-onset AF, assess the clinical utility of genetic testing, and discuss future directions for integrating genetic insights into personalized management strategies. Methods: We conducted a comprehensive analysis of recent studies, including genome-wide association studies and targeted sequencing efforts, that examined rare pathogenic variants and polygenic risk scores in early-onset AF. The review also considers emerging data on atrial cardiomyopathy and evaluates current guideline recommendations for genetic testing. Results: Data indicate that rare variants, particularly in genes such as TTN, LMNA, and KCNQ1, play a significant role in early-onset AF, with evidence suggesting an association between these mutations and adverse clinical outcomes. Polygenic risk scores further complement traditional risk factors, providing a more nuanced risk stratification. Despite these advances, challenges remain in the interpretation of variants of uncertain significance, cost-effectiveness, and the need for interdisciplinary collaboration in clinical implementation. Conclusions: Integrating genetic evaluation into the diagnostic and management framework of early-onset AF holds promise for improved risk stratification and personalized therapy. Future large-scale, multi-ethnic studies and ongoing refinement of genetic risk models are essential to overcome current limitations and enhance the clinical applicability of genetic testing in this rapidly evolving field.

Background Hypertrophic cardiomyopathy (HCM) is an important cause of mortality, caused by rare pathogenic variants (sarcomere-positive) in around one third of cases. Recent large genome-wide association studies (GWAS) highlight the important contributions of common genetic variation on HCM risk and heritability1-3. Polygenic scores (PGS) quantify the cumulative individual risk from common genetic variation, and may provide important clinical utility. Purpose The aim of this study is to generate PGS for HCM, and evaluate its performance in predicting HCM in the general population, HCM penetrance in sarcomere-positive carriers, and risk of adverse outcomes in individuals with HCM. Methods The PGS was generated using a Bayesian framework (PRS-CS) with individual SNP effect estimates derived from the largest published HCM GWAS (5900 cases and 68359 controls of European ancestry from 7 cohorts) and multi-trait analysis of GWAS (MTAG) (incorporating GWAS of genetically correlated cardiac magnetic resonance imaging (CMR) traits from 36203 White British individuals in the UK Biobank [UKB])1. Genome-wide PGS were calculated using an additive model for participants in two cohorts (UKB and 100,000 Genomes Project [GeL]). To evaluate the effect of PGS on penetrant HCM in sarcomere-positive carriers, we identified individuals with pathogenic or likely pathogenic variants in 8 definitive HCM-causing genes (MYBPC3, MYH7, TNNT2, TNNI3, TPM1, ACTC1, MYL3, and MYL2) in UKB and GeL. Results In 343,182 unrelated White British ancestry participants from the UK Biobank (UKB), PGS was associated with an increased risk of HCM (OR per PGS SD 2.3, P&amp;lt;2x10-16), with 75% of HCM cases having a PGS above the population mean (Figure 1A). Individuals with PGS in the top centile had a substantially increased risk of HCM compared with those in the median (OR 14.5, P&amp;lt;2x10-16) and bottom centile (OR 36.6, 3x10-25) (Figure 1B). PGS had significant effects on stratifying HCM penetrance in 640 sarcomere-positive carriers in the UKB (top vs. middle quintile HCM OR: 3.7, P 0.009), and risk of being a HCM case in 599 sarcomere-positive carriers in GeL (top vs. middle quintile HCM OR 9.5, P 4x10-5) (Figure 1C), highlighting the important interactive effect of common and rare genetic variants. Finally, PGS predicted risk of all-cause mortality and major adverse cardiovascular events (MACE) after HCM diagnosis in 382 cases in UKB (all-cause mortality: top vs. bottom quintile: HR 3.9, P 0.013; MACE: top vs. bottom quintile: HR 3.5, P 4.x10-4), and all-cause mortality in 683 cases in GeL (top vs. bottom quintile: HR 6.3, P 1x10-6) (Figure 1D). Conclusions We derive a PGS for HCM risk prediction, and demonstrate potential clinical utility in stratifying risk of penetrant HCM in sarcomere-positive carriers, and in predicting risk of adverse outcomes in individuals with HCM.Figure 1

&lt;div&gt;Abstract&lt;p&gt;Prostate cancer risk is influenced by rare and common germline variants. We examined the aggregate association of rare germline pathogenic/likely pathogenic/deleterious (P/LP/D) variants in &lt;i&gt;ATM, BRCA2, PALB2,&lt;/i&gt; and &lt;i&gt;NBN&lt;/i&gt; with a polygenic risk score (PRS) on prostate cancer risk among 1,796 prostate cancer cases (222 metastatic) and 1,424 controls of African ancestry. Relative to P/LP/D non-carriers at average genetic risk (33%–66% of PRS), men with low (0%–33%) and high (66%–100%) PRS had Odds Ratios (ORs) for overall prostate cancer of 2.08 [95% confidence interval (CI) = 0.58–7.49] and 18.06 (95% CI = 4.24–76.84) among P/LP/D carriers and 0.57 (95% CI = 0.46–0.71) and 3.02 (95% CI = 2.53–3.60) among non-carriers, respectively. The OR for metastatic prostate cancer was 2.73 (95% CI = 0.24–30.54) and 28.99 (95% CI = 4.39–191.43) among P/LP/D carriers and 0.54 (95% CI = 0.31–0.95) and 3.22 (95% CI = 2.20–4.73) among non-carriers, for men with low and high PRS, respectively. Lifetime absolute risks of overall prostate cancer increased with PRS (low to high) from 9.8% to 51.5% in P/LP/D carriers and 5.5% to 23.9% in non-carriers. Lifetime absolute risks of metastatic prostate cancer increased with PRS from 1.9% to 18.1% in P/LP/D carriers and 0.3% to 2.2% in non-carriers These findings suggest that assessment of prostate cancer risk for rare variant carriers should include PRS status.&lt;/p&gt;Significance:&lt;p&gt;These findings highlight the importance of considering rare and common variants to comprehensively assess prostate cancer risk in men of African ancestry.&lt;/p&gt;&lt;/div&gt;

Article 1: Epileptic encephalopathies are a devastating group of severe childhood epilepsy disorders for which the cause is often unknown. Here, we report a screen for de novo mutations in patients with 2 classical epileptic encephalopathies: infantile spasms (n = 149) and Lennox-Gastaut syndrome (n = 115). We sequenced the exomes of 264 probands, and their parents, and confirmed 329 de novo mutations. A likelihood analysis showed a significant excess of de novo mutations in the ∼4000 genes that are the most intolerant to functional genetic variation in the human population (P = 2.9 × 10(-3)). Among these are GABRB3, with de novo mutations in 4 patients, and ALG13, with the same de novo mutation in 2 patients; both genes show clear statistical evidence of association with epileptic encephalopathy. Given the relevant site-specific mutation rates, the probabilities of these outcomes occurring by chance are P = 4.1 × 10(-10) and P = 7.8 × 10(-12), respectively. Other genes with de novo mutations in this cohort include CACNA1A, CHD2, FLNA, GABRA1, GRIN1, GRIN2B, HNRNPU, IQSEC2, MTOR, and NEDD4L. Finally, we show that the de novo mutations observed are enriched in specific gene sets including genes regulated by the fragile X protein (P < 10(-8)), as has been reported previously for autism spectrum disorders. Article 2: Identifying genetic risk factors for highly heterogeneous disorders such as epilepsy remains challenging. Here, we present, to our knowledge, the largest whole-exome sequencing study of epilepsy to date, with more than 54,000 human exomes, comprising 20,979 deeply phenotyped patients from multiple genetic ancestry groups with diverse epilepsy subtypes and 33,444 controls, to investigate rare variants that confer disease risk. These analyses implicate 7 individual genes, 3 gene sets and 4 copy number variants at exome-wide significance. Genes encoding ion channels show strong association with multiple epilepsy subtypes, including epileptic encephalopathies and generalized and focal epilepsies, whereas most other gene discoveries are subtype specific, highlighting distinct genetic contributions to different epilepsies. Combining results from rare single-nucleotide/short insertion and deletion variants, copy number variants and common variants, we offer an expanded view of the genetic architecture of epilepsy, with growing evidence of convergence among different genetic risk loci on the same genes. Top candidate genes are enriched for roles in synaptic transmission and neuronal excitability, particularly postnatally and in the neocortex. We also identify shared rare variant risk between epilepsy and other neurodevelopmental disorders. Our data can be accessed via an interactive browser, hopefully facilitating diagnostic efforts and accelerating the development of follow-up studies. Article 3: Background: The epilepsies are highly heritable conditions that commonly follow complex inheritance. While monogenic causes have been identified in rare familial epilepsies, most familial epilepsies remain unsolved. We aimed to determine (1) whether common genetic variation contributes to familial epilepsy risk, and (2) whether that genetic risk is enriched in familial compared with nonfamilial (sporadic) epilepsies. Methods: Using common variants derived from the largest epilepsy genome-wide association study, we calculated polygenic risk scores (PRS) for patients with familial epilepsy (n = 1818 from 1181 families), their unaffected relatives (n = 771), sporadic patients (n = 1182), and population controls (n = 15,929). We also calculated separate PRS for genetic generalized epilepsy (GGE) and focal epilepsy. Statistical analyses used mixed-effects regression models to account for familial relatedness, sex, and ancestry. Findings: Patients with familial epilepsies had higher epilepsy PRS compared to population controls (OR 1·20, padj = 5 × 10-9), sporadic patients (OR 1·11, padj = 0.008), and their own unaffected relatives (OR 1·12, padj = 0.01). The top 1% of the PRS distribution was enriched 3.8-fold for individuals with familial epilepsy when compared to the lowest decile (padj = 5 × 10-11). Familial PRS enrichment was consistent across epilepsy type; overall, polygenic risk was greatest for the GGE clinical group. There was no significant PRS difference in familial cases with established rare variant genetic etiologies compared to unsolved familial cases. Interpretation: The aggregate effects of common genetic variants, measured as PRS, play an important role in explaining why some families develop epilepsy, why specific family members are affected while their relatives are not, and why families manifest specific epilepsy types. Polygenic risk contributes to the complex inheritance of the epilepsies, including in individuals with a known genetic etiology.

BackgroundMultiple common variants and also rare variants in monogenic risk genes such as BRCA2 and HOXB13 have been reported to be associated with risk of prostate cancer (PCa); however, the clinical setting in which germline genetic testing could be used for PCa diagnosis remains obscure. Herein, we tested the clinical utility of a 16 common variant–based polygenic risk score (PRS) that has been developed previously for Japanese men and also evaluated the frequency of PCa-associated rare variants in a prospective cohort of Japanese men undergoing prostate biopsy.MethodsA total of 1336 patients undergoing first prostate biopsy were included. PRS was calculated based on the genotype of 16 common variants, and sequencing of 8 prostate cancer–associated genes was performed by multiplex polymerase chain reaction based target sequencing. PRS was combined with clinical factors in logistic regression models to assess whether addition of PRS improves the prediction of biopsy positivity.ResultsThe top PRS decile was associated with an odds ratio of 4.10 (95% confidence interval = 2.46 to 6.86) with reference to the patients at average risk, and the estimated lifetime absolute risk approached 20%. Among the patients with prostate specific antigen 2-10 ng/mL who had prebiopsy magnetic resonance imaging, high PRS had an equivalent impact on biopsy positivity as a positive magnetic resonance imaging finding. Rare variants were detected in 19 (2.37%) and 7 (1.31%) patients with positive and negative biopsies, respectively, with BRCA2 variants being the most prevalent. There was no association between PRS and high-risk rare variants.ConclusionsGermline genetic testing could be clinically useful in both pre- and post-PSA screening settings.

Ankylosing spondylitis (AS) is a highly heritable common inflammatory arthritis that targets the spine and sacroiliac joints of the pelvis, causing pain and stiffness and leading eventually to joint fusion. Although previous studies have shown a strong association of IL23R with AS in white Europeans, similar studies in East Asian populations have shown no association with common variants of IL23R, suggesting either that IL23R variants have no role or that rare genetic variants contribute. The present study was undertaken to screen IL23R to identify rare variants associated with AS in Han Chinese. A 170-kb region containing IL23R and its flanking regions was sequenced in 50 patients with AS and 50 ethnically matched healthy control subjects from a Han Chinese population. In addition, the 30-kb region of peak association in white Europeans was sequenced in 650 patients with AS and 1,300 healthy controls. Validation genotyping was undertaken in 846 patients with AS and 1,308 healthy controls. We identified 1,047 variants, of which 729 were not found in the dbSNP genomic build 130. Several potentially functional rare variants in IL23R were identified, including one nonsynonomous single-nucleotide polymorphism (nsSNP), Gly(149) Arg (position 67421184 GA on chromosome 1). Validation genotyping showed that the Gly(149) Arg variant was associated with AS (odds ratio 0.61, P = 0.0054). This is the first study to implicate rare IL23R variants in the pathogenesis of AS. The results identified a low-frequency nsSNP with predicted loss-of-function effects that was protectively associated with AS in Han Chinese, suggesting that decreased function of the interleukin-23 (IL-23) receptor protects against AS. These findings further support the notion that IL-23 signaling has an important role in the pathogenesis of AS.

Early-onset drusen maculopathy (EODM) is a severe disease and can lead to advanced macular degeneration early in life; however, genetic and phenotypic characteristics of individuals with EODM are not well studied. To identify genotypic and phenotypic characteristics of individuals with EODM. This case-control study collected data from the European Genetic Database from September 2004 to October 2019. A total of 89 patients with EODM diagnosed at 55 years or younger and 91 patients with age-related macular degeneration (AMD) diagnosed at 65 years or older were included. Coding regions of CFH, CFI, C3, C9, CFB, ABCA4, PRPH2, TIMP3, and CTNNA1 genes were sequenced, genetic risk scores (GRS) were calculated based on 52 AMD-associated variants, and phenotypic characteristics on color fundus photographs were analyzed comparing patients with EODM and AMD. GRS, frequency of rare genetic complement variants, and phenotypic characteristics. This case-control study included 89 patients with EODM (mean [SD] age, 51.8 [8.7] years; 58 [65.2%] were female) and 91 patients with AMD (mean [SD] age, 77.6 [6.1] years; 45 [49.5%] female). At a mean (SD) age of 56.4 (7.3) years, 40 of 89 patients with EODM (44.9%) were affected by geographic atrophy or choroidal neovascularization. A lower GRS was observed in patients with EODM compared with patients with AMD (1.03 vs 1.60; P = .002), and 27 of 89 patients with EODM (30.3%) carried rare variants in the CFH gene compared with 7 of 91 patients with AMD (7.7%). Carriership of a rare CFH variant was associated with EODM (odds ratio, 7.2; 95% CI, 2.7-19.6; P < .001). A large macular drusen area (more than 50% covered with drusen) was observed in patients with EODM (24 of 162 eyes [14.8%]) compared with patients with AMD (9 of 164 eyes [5.5%]) (odds ratio, 4.57; 95% CI, 1.5-14.1; P = .008). A large proportion of patients with EODM in this study carried rare CFH variants, with most of the identified CFH variants clustered in the first 7 complement control protein domains affecting factor H and factor H-like 1. Because EODM frequently leads to advanced macular degeneration at an early age and can result in many years of vision loss, this study supports targeting the complement system and sequencing the CFH gene in patients with EODM to improve genetic counseling and future treatments for AMD.

Current software packages for the analysis and the simulations of rare variants are only available for binary and continuous traits. Ravages provides solutions in a single R package to perform rare variant association tests for multicategory, binary and continuous phenotypes, to simulate datasets under different scenarios and to compute statistical power. Association tests can be run in the whole genome thanks to C++ implementation of most of the functions, using either RAVA-FIRST, a recently developed strategy to filter and analyse genome-wide rare variants, or user-defined candidate regions. Ravages also includes a simulation module that generates genetic data for cases who can be stratified into several subgroups and for controls. Through comparisons with existing programmes, we show that Ravages complements existing tools and will be useful to study the genetic architecture of complex diseases. Ravages is available on the CRAN at https://cran.r-project.org/web/packages/Ravages/ and maintained on Github at https://github.com/genostats/Ravages.