Quantifying the polygenic contribution to variable expressivity in eleven rare genetic disorders

Investigating the sources of variable impact of pathogenic variants in monogenic metabolic conditions

Over three percent of people carry a dominant pathogenic variant, yet only a fraction of carriers develop disease. Disease phenotypes from carriers of variants in the same gene range from mild to severe. Here, we investigate underlying mechanisms for this heterogeneity: variable variant effect sizes, carrier polygenic backgrounds, and modulation of carrier effect by genetic background (marginal epistasis). We leveraged exomes and clinical phenotypes from the UK Biobank and the Mt. Sinai BioMe Biobank to identify carriers of pathogenic variants affecting cardiometabolic traits. We employed recently developed methods to study these cohorts, observing strong statistical support and clinical translational potential for all three mechanisms of variable carrier penetrance and disease severity. For example, scores from our recent model of variant pathogenicity were tightly correlated with phenotype amongst clinical variant carriers, they predicted effects of variants of unknown significance, and they distinguished gain- from loss-of-function variants. We also found that polygenic scores predicted phenotypes amongst pathogenic carriers and that epistatic effects can exceed main carrier effects by an order of magnitude.

Genetic modifiers of rare variants in monogenic developmental disorder loci

Rare damaging variants in a large number of genes are known to cause monogenic developmental disorders (DDs) and have also been shown to cause milder subclinical phenotypes in population cohorts. Here, we show that carrying multiple (2-5) rare damaging variants across 599 dominant DD genes has an additive adverse effect on numerous cognitive and socioeconomic traits in UK Biobank, which can be partially counterbalanced by a higher educational attainment polygenic score (EA-PGS). Phenotypic deviators from expected EA-PGS could be partly explained by the enrichment or depletion of rare DD variants. Among carriers of rare DD variants, those with a DD-related clinical diagnosis had a substantially lower EA-PGS and more severe phenotype than those without a clinical diagnosis. Our results suggest that the overall burden of both rare and common variants can modify the expressivity of a phenotype, which may then influence whether an individual reaches the threshold for clinical disease.

Evaluating and improving health equity and fairness of polygenic scores

Polygenic scores (PGSs) are quantitative metrics for predicting phenotypic values, such as human height or disease status. Some PGS methods require only summary statistics of a relevant genome-wide association study (GWAS) for their score. One such method is Lassosum, which inherits the model selection advantages of Lasso to select a meaningful subset of the GWAS single-nucleotide polymorphisms as predictors from their association statistics. However, even efficient scores like Lassosum, when derived from European-based GWASs, are poor predictors of phenotype for subjects of non-European ancestry; that is, they have limited portability to other ancestries. To increase the portability of Lassosum, when GWAS information and estimates of linkage disequilibrium are available for both ancestries, we propose Joint-Lassosum (JLS). In the simulation settings we explore, JLS provides more accurate PGSs compared to other methods, especially when measured in terms of fairness. In analyses of UK Biobank data, JLS was computationally more efficient but slightly less accurate than a Bayesian comparator, SDPRX. Like all PGS methods, JLS requires selection of predictors, which are determined by data-driven tuning parameters. We describe a new approach to selecting tuning parameters and note its relevance for model selection for any PGS. We also draw connections to the literature on algorithmic fairness and discuss how JLS can help mitigate fairness-related harms that might result from the use of PGSs in clinical settings. While no PGS method is likely to be universally portable, due to the diversity of human populations and unequal information content of GWASs for different ancestries, JLS is an effective approach for enhancing portability and reducing predictive bias.

Influences of sex chromosome aneuploidy on height, weight, and body mass index in human childhood and adolescence

Sex chromosome aneuploidies (SCAs) are collectively common conditions caused by carriage of a sex chromosome dosage other than XX for females and XY for males. Increases in sex chromosome dosage (SCD) have been shown to have an inverted-U association with height, but we lack combined studies of SCA effects on height and weight, and it is not known if any such effects vary with age. Here, we study norm-derived height and weight z-scores in 177 youth spanning 8 SCA karyotypes (XXX, XXY, XYY, XXXX, XXXY, XXYY, XXXXX, and XXXXY). We replicate a previously described inverted-U association between mounting SCD and height, and further show that there is also a muted version of this effect for weight: both phenotypes are elevated until SCD reaches 4 for females and 5 for males but decrease thereafter. We next use 266 longitudinal measures available from a subset of karyotypes (XXX, XXY, XYY, and XXYY) to show that mean height in these SCAs diverges further from norms with increasing age. As weight does not diverge from norms with increasing age, BMI decreases with increasing age. These findings extend our understanding of growth as an important clinical outcome in SCA, and as a key context for known effects of SCA on diverse organ systems that scale with body size.

Strategies for dissecting the complexity of neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) are associated with a wide range of clinical features, affecting multiple pathways involved in brain development and function. Recent advances in high-throughput sequencing have unveiled numerous genetic variants associated with NDDs, which further contribute to disease complexity and make it challenging to infer disease causation and underlying mechanisms. Herein, we review current strategies for dissecting the complexity of NDDs using model organisms, induced pluripotent stem cells, single-cell sequencing technologies, and massively parallel reporter assays. We further highlight single-cell CRISPR-based screening techniques that allow genomic investigation of cellular transcriptomes with high efficiency, accuracy, and throughput. Overall, we provide an integrated review of experimental approaches that can be applicable for investigating a broad range of complex disorders.

Principles and methods for transferring polygenic risk scores across global populations

Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.

Phenotypic and Genetic Factors Associated with Absence of Cardiomyopathy Symptoms in PLN:c.40_42delAGA Carriers

The c.40_42delAGA variant in the phospholamban gene (PLN) has been associated with dilated and arrhythmogenic cardiomyopathy, with up to 70% of carriers experiencing a major cardiac event by age 70. However, there are carriers who remain asymptomatic at older ages. To understand the mechanisms behind this incomplete penetrance, we evaluated potential phenotypic and genetic modifiers in 74 PLN:c.40_42delAGA carriers identified in 36,339 participants of the Lifelines population cohort. Asymptomatic carriers (N = 48) showed shorter QRS duration (- 5.73 ms, q value = 0.001) compared to asymptomatic non-carriers, an effect we could replicate in two different independent cohorts. Furthermore, symptomatic carriers showed a higher correlation (rPearson = 0.17) between polygenic predisposition to higher QRS (PGSQRS) and QRS (p value = 1.98 × 10-8), suggesting that the effect of the genetic variation on cardiac rhythm might be increased in symptomatic carriers. Our results allow for improved clinical interpretation for asymptomatic carriers, while our approach could guide future studies on genetic diseases with incomplete penetrance.

Polygenic risk for triglyceride levels in the presence of a high impact rare variant

BACKGROUND

Elevated triglyceride (TG) levels are a heritable and modifiable risk factor for cardiovascular disease and have well-established associations with common genetic variation captured in a polygenic risk score (PRS). In young adulthood, the 22q11.2 microdeletion conveys a 2-fold increased risk for mild-moderate hypertriglyceridemia. This study aimed to assess the role of the TG-PRS in individuals with this elevated baseline risk for mild-moderate hypertriglyceridemia.

METHODS

We studied a deeply phenotyped cohort of adults (n = 157, median age 34 years) with a 22q11.2 microdeletion and available genome sequencing, lipid level, and other clinical data. The association between a previously developed TG-PRS and TG levels was assessed using a multivariable regression model adjusting for effects of sex, BMI, and other covariates. We also constructed receiver operating characteristic (ROC) curves using logistic regression models to assess the ability of TG-PRS and significant clinical variables to predict mild-moderate hypertriglyceridemia status.

RESULTS

The TG-PRS was a significant predictor of TG-levels (p = 1.52E-04), along with male sex and BMI, in a multivariable model (pmodel = 7.26E-05). The effect of TG-PRS appeared to be slightly stronger in individuals with obesity (BMI ≥ 30) (beta = 0.4617) than without (beta = 0.1778), in a model unadjusted for other covariates (p-interaction = 0.045). Among ROC curves constructed, the inclusion of TG-PRS, sex, and BMI as predictor variables produced the greatest area under the curve (0.749) for classifying those with mild-moderate hypertriglyceridemia, achieving an optimal sensitivity and specificity of 0.746 and 0.707, respectively.

CONCLUSIONS

These results demonstrate that in addition to significant effects of sex and BMI, genome-wide common variation captured in a PRS also contributes to the variable expression of the 22q11.2 microdeletion with respect to elevated TG levels.

Subtyping Severe Hypercholesterolemia by Genetic Determinant to Stratify Risk of Coronary Artery Disease

BACKGROUND

Severe hypercholesterolemia, defined as LDL (low-density lipoprotein) cholesterol (LDL-C) measurement ≥190 mg/dL, is associated with increased risk for coronary artery disease (CAD). Causes of severe hypercholesterolemia include monogenic familial hypercholesterolemia, polygenic hypercholesterolemia, elevated lipoprotein(a) [Lp(a)] hypercholesteremia, polygenic hypercholesterolemia with elevated Lp(a) (two-hit), or nongenetic hypercholesterolemia. The added value of using a genetics approach to stratifying risk of incident CAD among those with severe hypercholesterolemia versus using LDL-C levels alone for risk stratification is not known.

METHODS

To determine whether risk stratification by genetic cause provided better 10-year incident CAD risk stratification than LDL-C level, a retrospective cohort study comparing incident CAD risk among severe hypercholesterolemia subtypes (genetic and nongenetic causes) was performed among 130 091 UK Biobank participants. Analyses were limited to unrelated, White British or Irish participants with available exome sequencing data. Participants with cardiovascular disease at baseline were excluded from analyses of incident CAD.

RESULTS

Of 130 091 individuals, 68 416 (52.6%) were women, and the mean (SD) age was 56.7 (8.0) years. Of the cohort, 9.0% met severe hypercholesterolemia criteria. Participants with LDL-C between 210 and 229 mg/dL and LDL-C ≥230 mg/dL showed modest increases in incident CAD risk relative to those with LDL-C between 190 and 209 mg/dL (210-229 mg/dL: hazard ratio [HR], 1.3 [95% CI, 1.1-1.7]; ≥230 mg/dL: HR, 1.3 [95% CI, 1.0-1.7]). In contrast, when risk was stratified by genetic subtype, monogenic familial hypercholesterolemia, elevated Lp(a), and two-hit hypercholesterolemia subtypes had increased rates of incident CAD relative to the nongenetic hypercholesterolemia subtype (monogenic familial hypercholesterolemia: HR, 2.3 [95% CI, 1.4-4.0]; elevated Lp(a): HR, 1.5 [95% CI, 1.2-2.0]; two-hit: HR, 1.9 [95% CI, 1.4-2.6]), while polygenic hypercholesterolemia did not.

CONCLUSIONS

Genetics-based subtyping for monogenic familial hypercholesterolemia and Lp(a) in those with severe hypercholesterolemia provided better stratification of 10-year incident CAD risk than LDL-C-based stratification.

Case reports of two siblings with autism spectrum disorder and 15q13.3 deletions

BACKGROUND

Copy number variations (CNVs) have been implicated in psychiatric and neurodevelopmental disorders. Especially, 15q13.3 deletions are strongly associated with autism spectrum disorder (ASD), intellectual disability (ID), schizophrenia (SCZ), attention deficithyperactivity disorder (ADHD), and mood disorder.

CASE PRESENTATION

We present two siblings with ASD. They had a father with bipolar disorder (BD). Patient 1 is a 21-year-old female with ASD and mild ID, who had language delay and repetitive behavior in childhood, social difficulties, and refused to go to school because of bullying. She was hospitalized in a psychiatric hospital several times. Patient 2 is a 19-year-old male with ASD and ADHD. He did not have developmental delay, but had social difficulties and impulsiveness, then refused to go to school because of bullying. He was treated by a psychiatrist for anxiety and disrupted sleep rhythms. Array comparative genomic hybridization was performed for the siblings and parents. 15q13.3 deletions were detected in the siblings and their healthy mothers. No other pathogenic CNVs were detected. We performed whole-genome sequencing of the family and identified 13 rare missense variants in brain-expressed genes, which may be responsible for the phenotypic differences between the siblings and their mother.

CONCLUSIONS

This study shows incomplete penetrance and variable expressivity in 15q13.3 deletions. We detected second-hit variants that may explain the phenotypic differences within this family. In addition, detecting 15q13.3 deletions may lead to early diagnosis and a better prognosis with careful follow-up.

DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data

DECIPHER (Database of Genomic Variation and Phenotype in Humans Using Ensembl Resources) shares candidate diagnostic variants and phenotypic data from patients with genetic disorders to facilitate research and improve the diagnosis, management, and therapy of rare diseases. The platform sits at the boundary between genomic research and the clinical community. DECIPHER aims to ensure that the most up-to-date data are made rapidly available within its interpretation interfaces to improve clinical care. Newly integrated cardiac case-control data that provide evidence of gene-disease associations and inform variant interpretation exemplify this mission. New research resources are presented in a format optimized for use by a broad range of professionals supporting the delivery of genomic medicine. The interfaces within DECIPHER integrate and contextualize variant and phenotypic data, helping to determine a robust clinico-molecular diagnosis for rare-disease patients, which combines both variant classification and clinical fit. DECIPHER supports discovery research, connecting individuals within the rare-disease community to pursue hypothesis-driven research.

The impact of rare protein coding genetic variation on adult cognitive function

Compelling evidence suggests that human cognitive function is strongly influenced by genetics. Here, we conduct a large-scale exome study to examine whether rare protein-coding variants impact cognitive function in the adult population (n = 485,930). We identify eight genes (ADGRB2, KDM5B, GIGYF1, ANKRD12, SLC8A1, RC3H2, CACNA1A and BCAS3) that are associated with adult cognitive function through rare coding variants with large effects. Rare genetic architecture for cognitive function partially overlaps with that of neurodevelopmental disorders. In the case of KDM5B we show how the genetic dosage of one of these genes may determine the variability of cognitive, behavioral and molecular traits in mice and humans. We further provide evidence that rare and common variants overlap in association signals and contribute additively to cognitive function. Our study introduces the relevance of rare coding variants for cognitive function and unveils high-impact monogenic contributions to how cognitive function is distributed in the normal adult population.

Candidate biomarkers from the integration of methylation and gene expression in discordant autistic sibling pairs

While the genetics of autism spectrum disorders (ASD) has been intensively studied, resulting in the identification of over 100 putative risk genes, the epigenetics of ASD has received less attention, and results have been inconsistent across studies. We aimed to investigate the contribution of DNA methylation (DNAm) to the risk of ASD and identify candidate biomarkers arising from the interaction of epigenetic mechanisms with genotype, gene expression, and cellular proportions. We performed DNAm differential analysis using whole blood samples from 75 discordant sibling pairs of the Italian Autism Network collection and estimated their cellular composition. We studied the correlation between DNAm and gene expression accounting for the potential effects of different genotypes on DNAm. We showed that the proportion of NK cells was significantly reduced in ASD siblings suggesting an imbalance in their immune system. We identified differentially methylated regions (DMRs) involved in neurogenesis and synaptic organization. Among candidate loci for ASD, we detected a DMR mapping to CLEC11A (neighboring SHANK1) where DNAm and gene expression were significantly and negatively correlated, independently from genotype effects. As reported in previous studies, we confirmed the involvement of immune functions in the pathophysiology of ASD. Notwithstanding the complexity of the disorder, suitable biomarkers such as CLEC11A and its neighbor SHANK1 can be discovered using integrative analyses even with peripheral tissues.

Hypomorphic Brca2 and Rad51c double mutant mice display Fanconi anemia, cancer and polygenic replication stress

The prototypic cancer-predisposition disease Fanconi Anemia (FA) is identified by biallelic mutations in any one of twenty-three FANC genes. Puzzlingly, inactivation of one Fanc gene alone in mice fails to faithfully model the pleiotropic human disease without additional external stress. Here we find that FA patients frequently display FANC co-mutations. Combining exemplary homozygous hypomorphic Brca2/Fancd1 and Rad51c/Fanco mutations in mice phenocopies human FA with bone marrow failure, rapid death by cancer, cellular cancer-drug hypersensitivity and severe replication instability. These grave phenotypes contrast the unremarkable phenotypes seen in mice with single gene-function inactivation, revealing an unexpected synergism between Fanc mutations. Beyond FA, breast cancer-genome analysis confirms that polygenic FANC tumor-mutations correlate with lower survival, expanding our understanding of FANC genes beyond an epistatic FA-pathway. Collectively, the data establish a polygenic replication stress concept as a testable principle, whereby co-occurrence of a distinct second gene mutation amplifies and drives endogenous replication stress, genome instability and disease.

Variation and impact of polygenic hematologic traits in monogenic sickle cell disease

Several of the complications observed in sickle cell disease (SCD) are influenced by variation in hematologic traits (HT), such as fetal hemoglobin (HbF) level and neutrophil count. Previous large-scale genome-wide association studies carried out in largely healthy individuals have identified thousands of variants associated with HT, which have then been used to develop multi-ancestry polygenic trait scores (PTS). Here, we tested whether these PTS associate with HT in SCD patients and if they can improve statistical models associated with SCD-related complications. In 2,056 SCD patients, we found that the PTS predicted less HT variance than in non-SCD individuals of African ancestry. This was particularly striking at the Duffy/DARC locus, where we observed an epistatic interaction between the SCD genotype and the Duffy null variant (rs2814778) that led to a two-fold weaker effect on neutrophil count. PTS for these HT which are measured as part of routine practice were not associated with complications in SCD. In contrast, we found that a simple PTS for HbF that includes only six variants explained a large fraction of the phenotypic variation (20.5-27.1%), associated with acute chest syndrome and stroke risk, and improved the statistical modeling of the vaso-occlusive crisis rate. Using Mendelian randomization, we found that increasing HbF by 4.8% reduces stroke risk by 39% (P=0.0006). Taken together, our results highlight the importance of validating PTS in large diseased populations before proposing their implementation in the context of precision medicine initiatives.

Wrestling with Social and Behavioral Genomics: Risks, Potential Benefits, and Ethical Responsibility

In this consensus report by a diverse group of academics who conduct and/or are concerned about social and behavioral genomics (SBG) research, the authors recount the often-ugly history of scientific attempts to understand the genetic contributions to human behaviors and social outcomes. They then describe what the current science-including genomewide association studies and polygenic indexes-can and cannot tell us, as well as its risks and potential benefits. They conclude with a discussion of responsible behavior in the context of SBG research. SBG research that compares individuals within a group according to a "sensitive" phenotype requires extra attention to responsible conduct and to responsible communication about the research and its findings. SBG research (1) on sensitive phenotypes that (2) compares two or more groups defined by (a) race, (b) ethnicity, or (c) genetic ancestry (where genetic ancestry could easily be misunderstood as race or ethnicity) requires a compelling justification to be conducted, funded, or published. All authors agree that this justification at least requires a convincing argument that a study's design could yield scientifically valid results; some authors would additionally require the study to have a socially favorable risk-benefit profile.

Unified views on variant impact across many diseases

Genomic studies of human disorders are often performed by distinct research communities (i.e., focused on rare diseases, common diseases, or cancer). Despite underlying differences in the mechanistic origin of different disease categories, these studies share the goal of identifying causal genomic events that are critical for the clinical manifestation of the disease phenotype. Moreover, these studies face common challenges, including understanding the complex genetic architecture of the disease, deciphering the impact of variants on multiple scales, and interpreting noncoding mutations. Here, we highlight these challenges in depth and argue that properly addressing them will require a more unified vocabulary and approach across disease communities. Toward this goal, we present a unified perspective on relating variant impact to various genomic disorders.

Genetically transitional disease: a new concept in genomic medicine

Traditional classification of genetic diseases as monogenic and polygenic has lagged far behind scientific progress. In this opinion article, we propose and define a new terminology, genetically transitional disease (GTD), referring to cases where a large-effect mutation is necessary, but not sufficient, to cause disease. This leads to a working disease nosology based on gradients of four types of genetic architecture: monogenic, polygenic, GTD, and mixed. We present four scenarios under which GTD may occur; namely, subsets of traditionally Mendelian disease, modifiable Tier 1 monogenic conditions, variable penetrance, and situations where a genetic mutational spectrum produces qualitatively divergent pathologies. The implications of the new nosology in precision medicine are discussed, in which therapeutic options may target the molecular cause or the disease phenotype.

Advances and Applications of Polygenic Scores for Coronary Artery Disease

Polygenic scores quantify inherited risk by integrating information from many common sites of DNA variation into a single number. Rapid increases in the scale of genetic association studies and new statistical algorithms have enabled development of polygenic scores that meaningfully measure-as early as birth-risk of coronary artery disease. These newer-generation polygenic scores identify up to 8% of the population with triple the normal risk based on genetic variation alone, and these individuals cannot be identified on the basis of family history or clinical risk factors alone. For those identified with increased genetic risk, evidence supports risk reduction with at least two interventions, adherence to a healthy lifestyle and cholesterol-lowering therapies, that can substantially reduce risk. Alongside considerable enthusiasm for the potential of polygenic risk estimation to enable a new era of preventive clinical medicine is recognition of a need for ongoing research into how best to ensure equitable performance across diverse ancestries, how and in whom to assess the scores in clinical practice, as well as randomized trials to confirm clinical utility.

Association of Supernumerary Sex Chromosome Aneuploidies With Venous Thromboembolism

IMPORTANCE

An increased risk of venous thromboembolism (VTE) has been reported in men with an additional sex chromosome. The association between other sex chromosome aneuploidies and VTE is not well characterized.

OBJECTIVE

To determine if sex chromosome aneuploidy is associated with VTE.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective cohort study of sex chromosome aneuploidy and VTE, performed by analyzing X- and Y-chromosome dosage and VTE incidence in 642 544 individuals from 2 population-scale biobanks: the US Geisinger MyCode Community Health Initiative (N = 154 519) and the UK Biobank (N = 488 025); analysis was limited to participants self-identified as White because of inadequate sample sizes for other race and ethnicity groups. A total of 108 461 unrelated MyCode participants with electronic health record follow-up ranging from September 1996 to December 2020 and 418 725 unrelated British and Irish UK Biobank participants who attended the baseline assessment between March 2006 and October 2010, with follow-up extending to November 2020, were included in analyses of VTE.

EXPOSURES

Sex chromosome aneuploidies.

MAIN OUTCOMES AND MEASURES

Individuals with 1 primary inpatient VTE diagnosis, 2 primary outpatient VTE diagnoses, or a self-reported VTE diagnosis were defined as VTE cases. P values were adjusted for multiple comparisons.

RESULTS

Identification of sex chromosome aneuploidy was undertaken among 642 544 individuals aged 18 to 90 years. Identification of a diagnosis of VTE was undertaken among 108 461 unrelated MyCode participants (65 565 [60.5%] female; mean age at last visit, 58.0 [SD, 17.6] years; median follow-up, 15.3 [IQR, 9.7] years) and among 418 725 unrelated UK Biobank participants (224 695 [53.7%] female; mean age at baseline interview, 56.9 [SD, 8.0] years; median follow-up, 12.0 [IQR, 1.6] years). Among MyCode participants, during 10 years of follow-up, 17 incident VTE events per 1353 person-years were detected among those with supernumerary sex chromosome aneuploidy (1.3% per person-year) compared with 2060 per 816 682 person-years among those with 46,XX or 46,XY (0.25% per person-year) (hazard ratio, 5.4 [95% CI, 3.4-8.7]; 10-year risk difference, 8.8% [95% CI, 4.2%-14.0%]; P < .001). Among UK Biobank participants, during 10 years of follow-up, 16 incident VTE events per 3803 person-years were detected among those with supernumerary sex chromosome aneuploidy (0.42% per person-year) compared with 4491 per 3 970 467 person-years among those with 46,XX or 46,XY (0.11% per person-year) (hazard ratio, 4.1 [95% CI, 2.5-6.7]; 10-year risk difference, 3.7% [95% CI, 1.4%-5.9%]; P < .001).

CONCLUSIONS AND RELEVANCE

Adults with supernumerary sex chromosome aneuploidies compared with 2 sex chromosomes had a small but statistically significant increased risk of VTE. Further research is needed to understand the clinical implications of this association.

Polygenic risk scores for the prediction of cardiometabolic disease

Cardiometabolic diseases contribute more to global morbidity and mortality than any other group of disorders. Polygenic risk scores (PRSs), the weighted summation of individually small-effect genetic variants, represent an advance in our ability to predict the development and complications of cardiometabolic diseases. This article reviews the evidence supporting the use of PRS in seven common cardiometabolic diseases: coronary artery disease (CAD), stroke, hypertension, heart failure and cardiomyopathies, obesity, atrial fibrillation (AF), and type 2 diabetes mellitus (T2DM). Data suggest that PRS for CAD, AF, and T2DM consistently improves prediction when incorporated into existing clinical risk tools. In other areas such as ischaemic stroke and hypertension, clinical application appears premature but emerging evidence suggests that the study of larger and more diverse populations coupled with more granular phenotyping will propel the translation of PRS into practical clinical prediction tools.

Phenotypic shift in copy number variants: Evidence in 16p11.2 duplication syndrome

PURPOSE

Recurrent 16p11.2 duplications produce a wide range of clinical outcomes with varying effects on cognition and social functioning. Family-based studies of copy number variants (CNVs) have revealed significant contributions of genomic background on variable expressivity. In this study, we measured the phenotypic effect of 16p11.2 duplications and quantified the modulating effect of familial background on cognitive and social outcomes.

METHODS

Genomic and clinical data were ascertained from 41 probands with a 16p11.2 duplication and their first-degree relatives. Paired comparisons were completed to determine the duplication's effect on expected vs actual performance on standardized tests of intelligence (IQ) and social functioning (Social Responsiveness Scale-2). Intraclass correlations between relatives and probands were also calculated.

RESULTS

Cognitive and social functioning were significantly lower among individuals with 16p11.2 duplications than their CNV-negative relatives, whereas intraclass correlations between the groups remained high for full-scale IQ and Social Responsiveness Scale-2 scores.

CONCLUSION

The 16p11.2 duplication confers deleterious effects on cognition and social functioning, whereas familial background significantly influences phenotypic expression of these traits. Understanding variable expressivity in CNV disorders has implications for anticipatory clinical care, particularly for individuals who receive a genetic diagnosis at an early age, long before the full scope of manifestations becomes evident.

A new 165-SNP low-density lipoprotein cholesterol polygenic risk score based on next generation sequencing outperforms previously published scores in routine diagnostics of familial hypercholesterolemia

Genetic diagnosis of familial hypercholesterolemia (FH) remains unexplained in 30 to 70% of patients after exclusion of monogenic disease. There is now a growing evidence that a polygenic burden significantly modulates LDL-cholesterol (LDL-c) concentrations. Several LDL-c polygenic risk scores (PRS) have been set up. However, the balance between their diagnosis performance and their practical use in routine practice is not clearly established. Consequently, we set up new PRS based on our routine panel for sequencing and compared their diagnostic performance with previously-published PRS. After a meta-analysis, four new PRS including 165 to 1633 SNP were setup using different softwares. They were established using two French control cohorts (MONA LISA n=1082 and FranceGenRef n=856). Then the explained LDL-c variance and the ability of each PRS to discriminate monogenic negative FH patients (M-) versus healthy controls were compared with 4 previously-described PRS in 785 unrelated FH patients. Between all PRS, the 165-SNP PRS developed with PLINK showed the best LDL-c explained variance (adjusted R²=0.19) and the best diagnosis abilities (AUROC=0.77, 95%CI=0.74-0.79): it significantly outperformed all the previously-published PRS (p<1 × 10^-4). By using a cut-off at the 75th percentile, 61% of M- patients exhibited a polygenic hypercholesterolemia with the 165-SNP PRS versus 48% with the previously published 12-SNP PRS (p =3.3 × 10^-6). These results were replicated using the UK biobank. This new 165-SNP PRS, usable in routine diagnosis, exhibits better diagnosis abilities for a polygenic hypercholesterolemia diagnosis. It would be a valuable tool to optimize referral for whole genome sequencing.

Cold shock domain-containing protein E1 is a posttranscriptional regulator of the LDL receptor

The low-density lipoprotein receptor (LDLR) controls cellular delivery of cholesterol and clears LDL from the bloodstream, protecting against atherosclerotic heart disease, the leading cause of death in the United States. We therefore sought to identify regulators of the LDLR beyond the targets of current therapies and known causes of familial hypercholesterolemia. We found that cold shock domain-containing protein E1 (CSDE1) enhanced hepatic LDLR messenger RNA (mRNA) decay via its 3' untranslated region and regulated atherogenic lipoproteins in vivo. Using parallel phenotypic genome-wide CRISPR interference screens in a tissue culture model, we identified 40 specific regulators of the LDLR that were not previously identified by observational human genetic studies. Among these, we demonstrated that, in HepG2 cells, CSDE1 regulated the LDLR at least as strongly as statins and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors. In addition, we showed that hepatic gene silencing of Csde1 treated diet-induced dyslipidemia in mice to a similar degree as Pcsk9 silencing. These results suggest the therapeutic potential of targeting CSDE1 to manipulate the posttranscriptional regulation of the LDLR mRNA for the prevention of cardiovascular disease. Our approach of modeling a clinically relevant phenotype in a forward genetic screen, followed by mechanistic pharmacologic dissection and in vivo validation, may serve as a generalizable template for the identification of therapeutic targets in other human disease states.

Identification of a Gain-of-Function LIPC Variant as a Novel Cause of Familial Combined Hypocholesterolemia

BACKGROUND

Atherosclerotic cardiovascular disease is the main cause of mortality worldwide and is strongly influenced by circulating low-density lipoprotein (LDL) cholesterol levels. Only a few genes causally related to plasma LDL cholesterol levels have been identified so far, and only 1 gene, ANGPTL3, has been causally related to combined hypocholesterolemia. Here, our aim was to elucidate the genetic origin of an unexplained combined hypocholesterolemia inherited in 4 generations of a French family.

METHODS

Using next-generation sequencing, we identified a novel dominant rare variant in the LIPC gene, encoding for hepatic lipase, which cosegregates with the phenotype. We characterized the impact of this LIPC-E97G variant on circulating lipid and lipoprotein levels in family members using nuclear magnetic resonance-based lipoprotein profiling and lipidomics. To uncover the mechanisms underlying the combined hypocholesterolemia, we used protein homology modeling, measured triglyceride lipase and phospholipase activities in cell culture, and studied the phenotype of APOE*3.Leiden.CETP mice after LIPC-E97G overexpression.

RESULTS

Family members carrying the LIPC-E97G variant had very low circulating levels of LDL cholesterol and high-density lipoprotein cholesterol, LDL particle numbers, and phospholipids. The lysophospholipids/phospholipids ratio was increased in plasma of LIPC-E97G carriers, suggestive of an increased lipolytic activity on phospholipids. In vitro and in vivo studies confirmed that the LIPC-E97G variant specifically increases the phospholipase activity of hepatic lipase through modification of an evolutionarily conserved motif that determines substrate access to the hepatic lipase catalytic site. Mice overexpressing human LIPC-E97G recapitulated the combined hypocholesterolemic phenotype of the family and demonstrated that the increased phospholipase activity promotes catabolism of triglyceride-rich lipoproteins by different extrahepatic tissues but not the liver.

CONCLUSIONS

We identified and characterized a novel rare variant in the LIPC gene in a family who presents with dominant familial combined hypocholesterolemia. This gain-of-function variant makes LIPC the second identified gene, after ANGPTL3, causally involved in familial combined hypocholesterolemia. Our mechanistic data highlight the critical role of hepatic lipase phospholipase activity in LDL cholesterol homeostasis and suggest a new LDL clearance mechanism.

Rare variants and the oligogenic architecture of autism

Most large-scale genetic studies of autism have focused on the discovery of genes by proving an enrichment of de novo mutations (DNMs) in autism probands or characterizing polygenic risk based on the association of common variants. We present evidence in support of an oligogenic model where two or more ultrarare mutations of more modest effect are preferentially transmitted to children with autism. Such private gene-disruptive mutations are enriched in families where there are multiple affected individuals, emerged two or three generations ago, and map to genes not previously associated with autism. Although no single gene has reached statistical significance, this class of variation should be considered along with genetic and nongenetic factors to better explain the etiology of this complex trait.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

Rare genetic variants in genes and loci linked to dominant monogenic developmental disorders cause milder related phenotypes in the general population

Many rare monogenic diseases are known to be caused by deleterious variants in thousands of genes, however the same variants can also be found in people without the associated clinical phenotypes. The penetrance of these monogenic variants is generally unknown in the wider population, as they are typically identified in small clinical cohorts of affected individuals and families with highly penetrant variants. Here, we investigated the phenotypic effect of rare, potentially deleterious variants in genes and loci where similar variants are known to cause monogenic developmental disorders (DDs) in a large population cohort. We used UK Biobank to investigate phenotypes associated with rare protein-truncating and missense variants in 599 monoallelic DDG2P genes by using whole-exome-sequencing data from ∼200,000 individuals and rare copy-number variants overlapping known DD loci by using SNP-array data from ∼500,000 individuals. We found that individuals with these likely deleterious variants had a mild DD-related phenotype, including lower fluid intelligence, slower reaction times, lower numeric memory scores, and longer pairs matching times compared to the rest of the UK Biobank cohort. They were also shorter, had a higher BMI, and had significant socioeconomic disadvantages: they were less likely to be employed or be able to work and had a lower income and higher deprivation index. Our findings suggest that many genes routinely tested within pediatric genetics have deleterious variants with intermediate penetrance that may cause lifelong sub-clinical phenotypes in the general adult population.

A Polygenic Score for Type 2 Diabetes Improves Risk Stratification Beyond Current Clinical Screening Factors in an Ancestrally Diverse Sample

A substantial proportion of the adult United States population with type 2 diabetes (T2D) are undiagnosed, calling into question the comprehensiveness of current screening practices, which primarily rely on age, family history, and body mass index (BMI). We hypothesized that a polygenic score (PGS) may serve as a complementary tool to identify high-risk individuals. The T2D polygenic score maintained predictive utility after adjusting for family history and combining genetics with family history led to even more improved disease risk prediction. We observed that the PGS was meaningfully related to age of onset with implications for screening practices: there was a linear and statistically significant relationship between the PGS and T2D onset (-1.3 years per standard deviation of the PGS). Evaluation of U.S. Preventive Task Force and a simplified version of American Diabetes Association screening guidelines showed that addition of a screening criterion for those above the 90th percentile of the PGS provided a small increase the sensitivity of the screening algorithm. Among T2D-negative individuals, the T2D PGS was associated with prediabetes, where each standard deviation increase of the PGS was associated with a 23% increase in the odds of prediabetes diagnosis. Additionally, each standard deviation increase in the PGS corresponded to a 43% increase in the odds of incident T2D at one-year follow-up. Using complications and forms of clinical intervention (i.e., lifestyle modification, metformin treatment, or insulin treatment) as proxies for advanced illness we also found statistically significant associations between the T2D PGS and insulin treatment and diabetic neuropathy. Importantly, we were able to replicate many findings in a Hispanic/Latino cohort from our database, highlighting the value of the T2D PGS as a clinical tool for individuals with ancestry other than European. In this group, the T2D PGS provided additional disease risk information beyond that offered by traditional screening methodologies. The T2D PGS also had predictive value for the age of onset and for prediabetes among T2D-negative Hispanic/Latino participants. These findings strengthen the notion that a T2D PGS could play a role in the clinical setting across multiple ancestries, potentially improving T2D screening practices, risk stratification, and disease management.

Contribution of rare variants in monogenic diabetes-genes to early-onset type 2 diabetes

AIM

This study investigated whether rare, deleterious variants in monogenic diabetes-genes are associated with early-onset type 2 diabetes (T2D).

METHODS

A nested case-control study was designed from 9,712 Italian patients with T2D. Individuals with age at diabetes onset ≤35 yrs (n=300; cases) or ≥65 yrs (n=300; controls) were selected and screened for variants in 27 monogenic diabetes-genes by targeted resequencing. Rare (minor allele frequency-MAF <1%) and possibly deleterious variants were collectively tested for association with early-onset T2D. The association of a genetic risk score (GRS) based on 17 GWAS-SNPs for T2D was also tested.

RESULTS

When all rare variants were considered together, each increased the risk of early-onset T2D by 65% (allelic OR =1.64, 95% CI: 1.08-2.48, p=0.02). Effects were similar when the 600 study participants were stratified according to their place of recruitment (Central-Southern Italy, 182 cases vs. 142 controls, or Rome urban area, 118 vs. 158, p for heterogeneity=0.53). Progressively less frequent variants showed increasingly stronger effects in the risk of early-onset T2D for those with MAF <0.001% (OR=6.34, 95% CI: 1.87-22.43, p=0.003). One unit of T2D-GRS significantly increased the risk of early-onset T2D (OR 1.09, 95% CI: 1.01-1.18; p=0.02). This association was stronger among rare variants carriers as compared to non-carriers (p=0.02).

CONCLUSION

Rare variants in monogenic-diabetes genes are associated with an increased risk of early-onset T2D, and interact with common T2D susceptibility variants in shaping it. These findings might help develop prediction tools to identify individuals at high risk of developing T2D in early adulthood.

Monogenic Versus Polygenic Forms of Hypercholesterolemia and Cardiovascular Risk: Are There Any Differences?

PURPOSE OF REVIEW

Common DNA variants with small effects work together to create susceptibility to polygenic hypercholesterolemia. Some clinicians wonder whether patients with polygenic hypercholesterolemia have less severe clinical features compared to patients with monogenic familial hypercholesterolemia (FH) caused by rare deleterious variants.

RECENT FINDINGS

Studies performed in cohorts of patients with both monogenic and polygenic hypercholesterolemia have assessed lipid levels, non-invasive markers of atherosclerosis, and clinical end points, including major adverse cardiovascular events. The totality of data suggests a gradient across genotypes. Specifically, individuals with polygenic hypercholesterolemia have deleterious phenotypes that are intermediate in severity between those in patients with monogenic hypercholesterolemia and in control subjects. Although clinical variables in patients with polygenic hypercholesterolemia are less severe than in those with monogenic hypercholesterolemia, cardiovascular risk is still very high in these patients compared to controls. Patients with polygenic hypercholesterolemia must be treated assertively.

The individual and global impact of copy-number variants on complex human traits

The impact of copy-number variations (CNVs) on complex human traits remains understudied. We called CNVs in 331,522 UK Biobank participants and performed genome-wide association studies (GWASs) between the copy number of CNV-proxy probes and 57 continuous traits, revealing 131 signals spanning 47 phenotypes. Our analysis recapitulated well-known associations (e.g., 1q21 and height), revealed the pleiotropy of recurrent CNVs (e.g., 26 and 16 traits for 16p11.2-BP4-BP5 and 22q11.21, respectively), and suggested gene functionalities (e.g., MARF1 in female reproduction). Forty-eight CNV signals (38%) overlapped with single-nucleotide polymorphism (SNP)-GWASs signals for the same trait. For instance, deletion of PDZK1, which encodes a urate transporter scaffold protein, decreased serum urate levels, while deletion of RHD, which encodes the Rhesus blood group D antigen, associated with hematological traits. Other signals overlapped Mendelian disorder regions, suggesting variable expressivity and broad impact of these loci, as illustrated by signals mapping to Rotor syndrome (SLCO1B1/3), renal cysts and diabetes syndrome (HNF1B), or Charcot-Marie-Tooth (PMP22) loci. Total CNV burden negatively impacted 35 traits, leading to increased adiposity, liver/kidney damage, and decreased intelligence and physical capacity. Thirty traits remained burden associated after correcting for CNV-GWAS signals, pointing to a polygenic CNV architecture. The burden negatively correlated with socio-economic indicators, parental lifespan, and age (survivorship proxy), suggesting a contribution to decreased longevity. Together, our results showcase how studying CNVs can expand biological insights, emphasizing the critical role of this mutational class in shaping human traits and arguing in favor of a continuum between Mendelian and complex diseases.

Contribution of schizophrenia polygenic burden to longitudinal phenotypic variance in 22q11.2 deletion syndrome

While the recurrent 22q11.2 deletion is one of the strongest genetic risk factors for schizophrenia (SCZ), variability of its associated neuropsychiatric endophenotypes reflects its incomplete penetrance for psychosis development. To assess whether this phenotypic variability is linked to common variants associated with SCZ, we studied the association between SCZ polygenic risk score (PRS) and longitudinally acquired phenotypic information of the Swiss 22q11.2DS cohort (n = 97, 50% females, mean age 17.7 yr, mean visit interval 3.8 yr). The SCZ PRS with the best predictive performance was ascertained in the Estonian Biobank (n = 201,146) with LDpred. The infinitesimal SCZ PRS model showed the strongest capacity in discriminating SCZ cases from controls with one SD difference in SCZ PRS corresponding to an odds ratio (OR) of 1.73 (95% CI 1.57-1.90, P = 1.47 × 10^-29). In 22q11.2 patients, random-effects ordinal regression modelling using longitudinal data showed SCZ PRS to have the strongest effect on social anhedonia (OR = 2.09, P = 0.0002), and occupational functioning (OR = 1.82, P = 0.0003) within the negative symptoms course, and dysphoric mood (OR = 2.00, P = 0.002) and stress intolerance (OR = 1.76, P = 0.0002) within the general symptoms course. Genetic liability for SCZ was additionally associated with full scale cognitive decline (β = -0.25, P = 0.02) and with longitudinal volumetric reduction of the right and left hippocampi (β = -0.28, P = 0.005; β = -0.23, P = 0.02, respectively). Our results indicate that the polygenic contribution to SCZ acts upon the threshold-lowering first hit (i.e., the deletion). It modifies the endophenotypes of 22q11.2DS and augments the derailment of developmental trajectories of negative and general symptoms, cognition, and hippocampal volume.

Polygenic Risk Scores in Alzheimer's Disease Genetics: Methodology, Applications, Inclusion, and Diversity

The success of genome-wide association studies (GWAS) completed in the last 15 years has reinforced a key fact: polygenic architecture makes a substantial contribution to variation of susceptibility to complex disease, including Alzheimer's disease. One straight-forward way to capture this architecture and predict which individuals in a population are most at risk is to calculate a polygenic risk score (PRS). This score aggregates the risk conferred across multiple genetic variants, ultimately representing an individual's predicted genetic susceptibility for a disease. PRS have received increasing attention after having been successfully used in complex traits. This has brought with it renewed attention on new methods which improve the accuracy of risk prediction. While these applications are initially informative, their utility is far from equitable: the majority of PRS models use samples heavily if not entirely of individuals of European descent. This basic approach opens concerns of health equity if applied inaccurately to other population groups, or health disparity if we fail to use them at all. In this review we will examine the methods of calculating PRS and some of their previous uses in disease prediction. We also advocate for, with supporting scientific evidence, inclusion of data from diverse populations in these existing and future studies of population risk via PRS.

Incomplete Penetrance and Variable Expressivity: From Clinical Studies to Population Cohorts

The same genetic variant found in different individuals can cause a range of diverse phenotypes, from no discernible clinical phenotype to severe disease, even among related individuals. Such variants can be said to display incomplete penetrance, a binary phenomenon where the genotype either causes the expected clinical phenotype or it does not, or they can be said to display variable expressivity, in which the same genotype can cause a wide range of clinical symptoms across a spectrum. Both incomplete penetrance and variable expressivity are thought to be caused by a range of factors, including common variants, variants in regulatory regions, epigenetics, environmental factors, and lifestyle. Many thousands of genetic variants have been identified as the cause of monogenic disorders, mostly determined through small clinical studies, and thus, the penetrance and expressivity of these variants may be overestimated when compared to their effect on the general population. With the wealth of population cohort data currently available, the penetrance and expressivity of such genetic variants can be investigated across a much wider contingent, potentially helping to reclassify variants that were previously thought to be completely penetrant. Research into the penetrance and expressivity of such genetic variants is important for clinical classification, both for determining causative mechanisms of disease in the affected population and for providing accurate risk information through genetic counseling. A genotype-based definition of the causes of rare diseases incorporating information from population cohorts and clinical studies is critical for our understanding of incomplete penetrance and variable expressivity. This review examines our current knowledge of the penetrance and expressivity of genetic variants in rare disease and across populations, as well as looking into the potential causes of the variation seen, including genetic modifiers, mosaicism, and polygenic factors, among others. We also considered the challenges that come with investigating penetrance and expressivity.

Towards precision medicine in heart failure

The number of therapies for heart failure (HF) with reduced ejection fraction has nearly doubled in the past decade. In addition, new therapies for HF caused by hypertrophic and infiltrative disease are emerging rapidly. Indeed, we are on the verge of a new era in HF in which insights into the biology of myocardial disease can be matched to an understanding of the genetic predisposition in an individual patient to inform precision approaches to therapy. In this Review, we summarize the biology of HF, emphasizing the causal relationships between genetic contributors and traditional structure-based remodelling outcomes, and highlight the mechanisms of action of traditional and novel therapeutics. We discuss the latest advances in our understanding of both the Mendelian genetics of cardiomyopathy and the complex genetics of the clinical syndrome presenting as HF. In the phenotypic domain, we discuss applications of machine learning for the subcategorization of HF in ways that might inform rational prescribing of medications. We aim to bridge the gap between the biology of the failing heart, its diverse clinical presentations and the range of medications that we can now use to treat it. We present a roadmap for the future of precision medicine in HF.

How rare and common risk variation jointly affect liability for autism spectrum disorder

BACKGROUND

Genetic studies have implicated rare and common variations in liability for autism spectrum disorder (ASD). Of the discovered risk variants, those rare in the population invariably have large impact on liability, while common variants have small effects. Yet, collectively, common risk variants account for the majority of population-level variability. How these rare and common risk variants jointly affect liability for individuals requires further study.

METHODS

To explore how common and rare variants jointly affect liability, we assessed two cohorts of ASD families characterized for rare and common genetic variations (Simons Simplex Collection and Population-Based Autism Genetics and Environment Study). We analyzed data from 3011 affected subjects, as well as two cohorts of unaffected individuals characterized for common genetic variation: 3011 subjects matched for ancestry to ASD subjects and 11,950 subjects for estimating allele frequencies. We used genetic scores, which assessed the relative burden of common genetic variation affecting risk of ASD (henceforth "burden"), and determined how this burden was distributed among three subpopulations: ASD subjects who carry a potentially damaging variant implicated in risk of ASD ("PDV carriers"); ASD subjects who do not ("non-carriers"); and unaffected subjects who are assumed to be non-carriers.

RESULTS

Burden harbored by ASD subjects is stochastically greater than that harbored by control subjects. For PDV carriers, their average burden is intermediate between non-carrier ASD and control subjects. Both carrier and non-carrier ASD subjects have greater burden, on average, than control subjects. The effects of common and rare variants likely combine additively to determine individual-level liability.

LIMITATIONS

Only 305 ASD subjects were known PDV carriers. This relatively small subpopulation limits this study to characterizing general patterns of burden, as opposed to effects of specific PDVs or genes. Also, a small fraction of subjects that are categorized as non-carriers could be PDV carriers.

CONCLUSIONS

Liability arising from common and rare risk variations likely combines additively to determine risk of any individual diagnosed with ASD. On average, ASD subjects carry a substantial burden of common risk variation, even if they also carry a rare PDV affecting risk.

Advances in understanding the pathogenesis of hereditary macrothrombocytopenia

Low platelet count, or thrombocytopenia, is a common haematological abnormality, with a wide differential diagnosis, which may represent a clinically significant underlying pathology. Macrothrombocytopenia, the presence of large platelets in combination with thrombocytopenia, can be acquired or hereditary and indicative of a complex disorder. In this review, we discuss the interpretation of platelet count and volume measured by automated haematology analysers and highlight some important technical considerations relevant to the analysis of blood samples with macrothrombocytopenia. We review how large cohorts, such as the UK Biobank and INTERVAL studies, have enabled an accurate description of the distribution and co-variation of platelet parameters in adult populations. We discuss how genome-wide association studies have identified hundreds of genetic associations with platelet count and mean platelet volume, which in aggregate can explain large fractions of phenotypic variance, consistent with a complex genetic architecture and polygenic inheritance. Finally, we describe the large genetic diagnostic and discovery programmes, which, simultaneously to genome-wide association studies, have expanded the repertoire of genes and variants associated with extreme platelet phenotypes. These have advanced our understanding of the pathogenesis of hereditary macrothrombocytopenia and support a future clinical diagnostic strategy that utilises genotype alongside clinical and laboratory phenotype data.

Prognostic value of polygenic risk scores for adults with psychosis

Polygenic risk scores (PRS) summarize genetic liability to a disease at the individual level, and the aim is to use them as biomarkers of disease and poor outcomes in real-world clinical practice. To date, few studies have assessed the prognostic value of PRS relative to standards of care. Schizophrenia (SCZ), the archetypal psychotic illness, is an ideal test case for this because the predictive power of the SCZ PRS exceeds that of most other common diseases. Here, we analyzed clinical and genetic data from two multi-ethnic cohorts totaling 8,541 adults with SCZ and related psychotic disorders, to assess whether the SCZ PRS improves the prediction of poor outcomes relative to clinical features captured in a standard psychiatric interview. For all outcomes investigated, the SCZ PRS did not improve the performance of predictive models, an observation that was generally robust to divergent case ascertainment strategies and the ancestral background of the study participants.

Clinical, pathological and genetic characteristics of Perry disease-new cases and literature review

BACKGROUND AND PURPOSE

Perry disease (or Perry syndrome) is an autosomal dominant neurodegenerative disorder characterized by parkinsonism, neuropsychiatric symptoms, central hypoventilation, weight loss and distinct TDP-43 pathology. It is caused by mutations of the DCTN1 gene encoding an essential component of axonal transport. The objectives were to provide the current state of knowledge on clinical, pathological and genetic aspects of Perry disease, as well as practical suggestions for the management of the disease.

METHODS

Data on new patients from New Zealand, Poland and Colombia were collected, including autopsy report. Also all of the published papers since the original work by Perry in 1975 were gathered and analyzed.

RESULTS

Parkinsonism was symmetrical, progressed rapidly and was poorly responsive to L-Dopa; nonetheless, a trial with high doses of L-Dopa is warranted. Depression was severe, associated with suicidal ideations, and benefited from antidepressants and L-Dopa. Respiratory symptoms were the leading cause of death, and artificial ventilation or a diaphragm pacemaker prolonged survival. Weight loss occurred in most patients and was of multifactorial etiology. Autonomic dysfunction was frequent but underdiagnosed. There was a clinical overlap with other neurodegenerative disorders. An autopsy showed distinctive pallidonigral degeneration with TDP-43 pathology. Genetic testing provided evidence of a common founder for two families. There was striking phenotypic variability in DCTN1-related disorders. It is hypothesized that oligogenic or polygenic inheritance is at play.

CONCLUSIONS

Perry disease and other DCTN1-related diseases are increasingly diagnosed worldwide. Relatively effective symptomatic treatments are available. Further studies are needed to pave the way toward curative/gene therapy.

Three decades of ASD genetics: Building a foundation for neurobiological understanding and treatment

Methodological advances over the last three decades have led to a profound transformation in our understanding of the genetic origins of neuropsychiatric disorders. This is exemplified by the study of autism spectrum disorders (ASD) for which microarrays, whole exome sequencing (WES) and whole genome sequencing (WGS) have yielded over a hundred causal loci. Genome-wide association studies (GWAS) in ASD have also been fruitful, identifying 5 genome-wide significant loci thus far and demonstrating a substantial role for polygenic inherited risk. Approaches rooted in systems biology and functional genomics have increasingly placed genes implicated by risk variants into biological context. Genetic risk affects a finite group of cell-types and biological processes, converging primarily on early stages of brain development (though, the expression of many risk genes persists through childhood). Coupled with advances in stem cell-based human in vitro model systems, these findings provide a basis for developing mechanistic models of disease pathophysiology.

Contextualizing genetic risk score for disease screening and rare variant discovery

Studies of the genetic basis of complex traits have demonstrated a substantial role for common, small-effect variant polygenic burden (PB) as well as large-effect variants (LEV, primarily rare). We identify sufficient conditions in which GWAS-derived PB may be used for well-powered rare pathogenic variant discovery or as a sample prioritization tool for whole-genome or exome sequencing. Through extensive simulations of genetic architectures and generative models of disease liability with parameters informed by empirical data, we quantify the power to detect, among cases, a lower PB in LEV carriers than in non-carriers. Furthermore, we uncover clinically useful conditions wherein the risk derived from the PB is comparable to the LEV-derived risk. The resulting summary-statistics-based methodology (with publicly available software, PB-LEV-SCAN) makes predictions on PB-based LEV screening for 36 complex traits, which we confirm in several disease datasets with available LEV information in the UK Biobank, with important implications on clinical decision-making.

Williams syndrome

Williams syndrome (WS) is a relatively rare microdeletion disorder that occurs in as many as 1:7,500 individuals. WS arises due to the mispairing of low-copy DNA repetitive elements at meiosis. The deletion size is similar across most individuals with WS and leads to the loss of one copy of 25-27 genes on chromosome 7q11.23. The resulting unique disorder affects multiple systems, with cardinal features including but not limited to cardiovascular disease (characteristically stenosis of the great arteries and most notably supravalvar aortic stenosis), a distinctive craniofacial appearance, and a specific cognitive and behavioural profile that includes intellectual disability and hypersociability. Genotype-phenotype evidence is strongest for ELN, the gene encoding elastin, which is responsible for the vascular and connective tissue features of WS, and for the transcription factor genes GTF2I and GTF2IRD1, which are known to affect intellectual ability, social functioning and anxiety. Mounting evidence also ascribes phenotypic consequences to the deletion of BAZ1B, LIMK1, STX1A and MLXIPL, but more work is needed to understand the mechanism by which these deletions contribute to clinical outcomes. The age of diagnosis has fallen in regions of the world where technological advances, such as chromosomal microarray, enable clinicians to make the diagnosis of WS without formally suspecting it, allowing earlier intervention by medical and developmental specialists. Phenotypic variability is considerable for all cardinal features of WS but the specific sources of this variability remain unknown. Further investigation to identify the factors responsible for these differences may lead to mechanism-based rather than symptom-based therapies and should therefore be a high research priority.

[Genetic risk factors and their influence on neural development in autism spectrum disorders]

Genetic risk factors and their influence on neural development in autism spectrum disorders Abstract. Abstract. Autism spectrum disorders are etiologically based on genetic and specific gene x biologically relevant environmental risk factors. They are diagnosed based on behavioral characteristics, such as impaired social communication and stereotyped, repetitive behavior and sensory as well as special interests. The genetic background is heterogeneous, i. e., it comprises diverse genetic risk factors across the disorder and high interindividual differences of specific genetic risk factors. Nevertheless, risk factors converge regarding underlying biological mechanisms and shared pathways, which likely cause the autism-specific behavioral characteristics. The current selective literature review summarizes differential genetic risk factors and focuses particularly on mechanisms and pathways currently being discussed by international research. In conclusion, clinically relevant aspects and open translational research questions are presented.

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.