Polygenic risk score analysis for amyotrophic lateral sclerosis leveraging cognitive performance, educational attainment and schizophrenia

Genetic testing for monogenic forms of motor neuron disease/amyotrophic lateral sclerosis in unaffected family members

Motor neuron disease (MND), also referred to as amyotrophic lateral sclerosis (ALS), is a monogenic disease in a minority of cases, with autosomal dominant inheritance. Increasing numbers of people with MND are requesting genetic testing, and indeed receiving a genetic diagnosis. Consequently, requests for genetic counselling and predictive testing (i.e. of unaffected family members) are similarly expected to rise, alongside pre-symptomatic clinical trials. Despite this, there is no evidence-based guideline for predictive genetic testing in MND. This paper provides an overview of the genomic basis of MND, focusing specifically on the most common monogenic causes of MND. It then lays out the complexities of MND predictive testing, including the genetic landscape characterised by incomplete penetrance, clinical and genetic heterogeneity, and an oligogenic mechanism of pathogenesis in some cases. Additionally, there is limited research on the psychosocial impact of predictive genetic testing for MND, with studies suggesting potential difficulty in adjusting to the news, in part due to a lack of support and follow-up. This underscores a case for evidence-based, disease-specific guidance for predictive testing in MND.

Improving prediction models of amyotrophic lateral sclerosis (ALS) using polygenic, pre-existing conditions, and survey-based risk scores in the UK Biobank

BACKGROUND AND OBJECTIVES

Amyotrophic lateral sclerosis (ALS) causes profound impairments in neurological function, and a cure for this devastating disease remains elusive. This study aimed to identify pre-disposing genetic, phenotypic, and exposure-related factors for amyotrophic lateral sclerosis using multi-modal data and assess their joint predictive potential.

METHODS

Utilizing data from the UK (United Kingdom) Biobank, we analyzed an unrelated set of 292 ALS cases and 408,831 controls of European descent. Two polygenic risk scores (PRS) are constructed: "GWAS Hits PRS" and "PRS-CS," reflecting oligogenic and polygenic ALS risk profiles, respectively. Time-restricted phenome-wide association studies (PheWAS) were performed to identify pre-existing conditions increasing ALS risk, integrated into phenotypic risk scores (PheRS). A poly-exposure score ("PXS") captures the influence of environmental exposures measured through survey questionnaires. We evaluate the performance of these scores for predicting ALS incidence and stratifying risk, adjusting for baseline demographic covariates.

RESULTS

Both PRSs modestly predicted ALS diagnosis but with increased predictive power when combined (covariate-adjusted receiver operating characteristic [AAUC] = 0.584 [0.525, 0.639]). PheRS incorporated diagnoses 1 year before ALS onset (PheRS1) modestly discriminated cases from controls (AAUC = 0.515 [0.472, 0.564]). The "PXS" did not significantly predict ALS. However, a model incorporating PRSs and PheRS1 improved the prediction of ALS (AAUC = 0.604 [0.547, 0.667]), outperforming a model combining all risk scores. This combined risk score identified the top 10% of risk score distribution with a fourfold higher ALS risk (95% CI [2.04, 7.73]) versus those in the 40%-60% range.

DISCUSSION

By leveraging UK Biobank data, our study uncovers pre-disposing ALS factors, highlighting the improved effectiveness of multi-factorial prediction models to identify individuals at highest risk for ALS.

Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations

BACKGROUND

The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural variants, and aneuploidy. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, raising the possibility of screening embryos for their risk of polygenic diseases such as breast cancer, hypertension, diabetes, or schizophrenia. Despite a heated debate around this new technology, called polygenic embryo screening (PES; also PGT-P), it is already available to IVF patients in some countries. Several articles have studied epidemiological, clinical, and ethical perspectives on PES; however, a comprehensive, principled review of this emerging field is missing.

OBJECTIVE AND RATIONALE

This review has four main goals. First, given the interdisciplinary nature of PES studies, we aim to provide a self-contained educational background about PES to reproductive specialists interested in the subject. Second, we provide a comprehensive and critical review of arguments for and against the introduction of PES, crystallizing and prioritizing the key issues. We also cover the attitudes of IVF patients, clinicians, and the public towards PES. Third, we distinguish between possible future groups of PES patients, highlighting the benefits and harms pertaining to each group. Finally, our review, which is supported by ESHRE, is intended to aid healthcare professionals and policymakers in decision-making regarding whether to introduce PES in the clinic, and if so, how, and to whom.

SEARCH METHODS

We searched for PubMed-indexed articles published between 1/1/2003 and 1/3/2024 using the terms 'polygenic embryo screening', 'polygenic preimplantation', and 'PGT-P'. We limited the review to primary research papers in English whose main focus was PES for medical conditions. We also included papers that did not appear in the search but were deemed relevant.

OUTCOMES

The main theoretical benefit of PES is a reduction in lifetime polygenic disease risk for children born after screening. The magnitude of the risk reduction has been predicted based on statistical modelling, simulations, and sibling pair analyses. Results based on all methods suggest that under the best-case scenario, large relative risk reductions are possible for one or more diseases. However, as these models abstract several practical limitations, the realized benefits may be smaller, particularly due to a limited number of embryos and unclear future accuracy of the risk estimates. PES may negatively impact patients and their future children, as well as society. The main personal harms are an unindicated IVF treatment, a possible reduction in IVF success rates, and patient confusion, incomplete counselling, and choice overload. The main possible societal harms include discarded embryos, an increasing demand for 'designer babies', overemphasis of the genetic determinants of disease, unequal access, and lower utility in people of non-European ancestries. Benefits and harms will vary across the main potential patient groups, comprising patients already requiring IVF, fertile people with a history of a severe polygenic disease, and fertile healthy people. In the United States, the attitudes of IVF patients and the public towards PES seem positive, while healthcare professionals are cautious, sceptical about clinical utility, and concerned about patient counselling.

WIDER IMPLICATIONS

The theoretical potential of PES to reduce risk across multiple polygenic diseases requires further research into its benefits and harms. Given the large number of practical limitations and possible harms, particularly unnecessary IVF treatments and discarded viable embryos, PES should be offered only within a research context before further clarity is achieved regarding its balance of benefits and harms. The gap in attitudes between healthcare professionals and the public needs to be narrowed by expanding public and patient education and providing resources for informative and unbiased genetic counselling.

Unraveling the multifaceted insights into amyotrophic lateral sclerosis: Genetic underpinnings, pathogenesis, and therapeutic horizons

Amyotrophic Lateral Sclerosis (ALS), a progressive neurodegenerative disease, primarily impairs upper and lower motor neurons, leading to debilitating motor dysfunction and eventually respiratory failure, widely known as Lou Gehrig's disease. ALS presents with diverse symptomatology, including dysarthria, dysphagia, muscle atrophy, and hyperreflexia. The prevalence of ALS varies globally, with incidence rates ranging from 1.5 to 3.8 per 100,000 individuals, significantly affecting populations aged 45-80. A complex interplay of genetic and environmental factors underpins ALS pathogenesis. Key genetic contributors include mutations in chromosome 9 open reading frame 72 (C9ORF72), superoxide dismutase type 1 (SOD1), Fusedin sarcoma (FUS), and TAR DNA-binding protein (TARDBP) genes, accounting for a considerable fraction of both familial (fALS) and sporadic (sALS) cases. The disease mechanism encompasses aberrant protein folding, mitochondrial dysfunction, oxidative stress, excitotoxicity, and neuroinflammation, contributing to neuronal death. This review consolidates current insights into ALS's multifaceted etiology, highlighting the roles of environmental exposures (e.g., toxins, heavy metals) and their interaction with genetic predispositions. We emphasize the polygenic nature of ALS, where multiple genetic variations cumulatively influence disease susceptibility and progression. This aspect underscores the challenges in ALS diagnosis, which currently lacks specific biomarkers and relies on symptomatology and familial history. Therapeutic strategies for ALS, still in nascent stages, involve symptomatic management and experimental approaches targeting molecular pathways implicated in ALS pathology. Gene therapy, focusing on specific ALS mutations, and stem cell therapy emerge as promising avenues. However, effective treatments remain elusive, necessitating a deeper understanding of ALS's genetic architecture and the development of targeted therapies based on personalized medicine principles. This review aims to provide a comprehensive understanding of ALS, encouraging further research into its complex genetic underpinnings and the development of innovative, effective treatment modalities.

Recurrent stroke prediction by applying a stroke polygenic risk score in the Japanese population

Background

Recently, various polygenic risk score (PRS)-based methods were developed to improve stroke prediction. However, current PRSs (including cross-ancestry PRS) poorly predict recurrent stroke. Here, we aimed to determine whether the best PRS for Japanese individuals can also predict stroke recurrence in this population by extensively comparing the methods and maximizing the predictive performance for stroke onset.

Methods

We used data from the BioBank Japan (BBJ) 1st cohort (n=179,938) to derive and optimize the PRSs using a 10-fold cross-validation. We integrated the optimized PRSs for multiple traits, such as vascular risk factors and stroke subtypes to generate a single PRS using the meta-scoring approach (metaGRS). We used an independent BBJ 2nd cohort (n=41,929) as a test sample to evaluate the association of the metaGRS with stroke and recurrent stroke.

Results

We analyzed recurrent stroke cases (n=174) and non-recurrent stroke controls (n=1,153) among subjects within the BBJ 2nd cohort. After adjusting for known risk factors, metaGRS was associated with stroke recurrence (adjusted OR per SD 1.18 [95% CI: 1.00-1.39, p=0.044]), although no significant correlation was observed with the published PRSs. We administered three distinct tests to consider the potential index event bias; however, the outcomes derived from these examinations did not provide any significant indication of the influence of index event bias. The high metaGRS group without a history of hypertension had a higher risk of stroke recurrence than that of the low metaGRS group (adjusted OR 2.24 [95% CI: 1.07-4.66, p=0.032]). However, this association was weak in the hypertension group (adjusted OR 1.21 [95% CI: 0.69-2.13, p=0.50]).

Conclusions

The metaGRS developed in a Japanese cohort predicted stroke recurrence in an independent cohort of patients. In particular, it predicted an increased risk of recurrence among stroke patients without hypertension. These findings provide clues for additional genetic risk stratification and help in developing personalized strategies for stroke recurrence prevention.

Improving prediction models of amyotrophic lateral sclerosis (ALS) using polygenic, pre-existing conditions, and survey-based risk scores in the UK Biobank

Background and Objectives

Amyotrophic lateral sclerosis (ALS) causes profound impairments in neurological function and a cure for this devastating disease remains elusive. Early detection and risk stratification are crucial for timely intervention and improving patient outcomes. This study aimed to identify predisposing genetic, phenotypic, and exposure-related factors for Amyotrophic lateral sclerosis using multi-modal data and assess their joint predictive potential.

Methods

Utilizing data from the UK Biobank, we analyzed an unrelated set of 292 ALS cases and 408,831 controls of European descent. Two polygenic risk scores (PRS) are constructed: "GWAS Hits PRS" and "PRS-CS," reflecting oligogenic and polygenic ALS risk profiles, respectively. Time-restricted phenome-wide association studies (PheWAS) were performed to identify pre-existing conditions increasing ALS risk, integrated into phenotypic risk scores (PheRS). A poly-exposure score ("PXS") captures the influence of environmental exposures measured through survey questionnaires. We evaluate the performance of these scores for predicting ALS incidence and stratifying risk, adjusting for baseline demographic covariates.

Results

Both PRSs modestly predicted ALS diagnosis, but with increased predictive power when combined (covariate-adjusted receiver operating characteristic [AAUC] = 0.584 [0.525, 0.639]). PheRS incorporated diagnoses 1 year before ALS onset (PheRS1) modestly discriminated cases from controls (AAUC = 0.515 [0.472, 0.564]). The "PXS" did not significantly predict ALS. However, a model incorporating PRSs and PheRS1 improved prediction of ALS (AAUC = 0.604 [0.547, 0.667]), outperforming a model combining all risk scores. This combined risk score identified the top 10% of risk score distribution with a 4-fold higher ALS risk (95% CI: [2.04, 7.73]) versus those in the 40%-60% range.

Discussions

By leveraging UK Biobank data, our study uncovers predisposing ALS factors, highlighting the improved effectiveness of multi-factorial prediction models to identify individuals at highest risk for ALS.

Biochemical parameters as a tool to assess the nutritional status of patients with amyotrophic lateral sclerosis

Background

The research aimed to analyze blood biochemical parameters in patients with amyotrophic lateral sclerosis and to determine whether they can be used to assess their nutritional status.

Methods

The study included 45 patients diagnosed with amyotrophic lateral sclerosis (ALS): 28 (62.2%) were men and 17 (37.8%) were women. The mean age of the study participants was 50.69 ± 7.24 years. The control group consisted of 30 practically healthy individuals.

Results

Compared with practically healthy individuals, patients with ALS had significantly lower blood parameters, including total lymphocyte count (1.49 ± 0.11 vs. 2.86 ± 0.25, p < 0.05), total protein (60.55 ± 2.38 vs. 77.80 ± 4.41, p < 0.05), albumin (33.70 ± 2.03 vs. 46.49 ± 3.22, p < 0.05), urea (3.09 ± 0.36 vs. 5.37 ± 0.50, p < 0.05), creatinine (51.28 ± 4.42 vs. 70.91 ± 5.13, p < 0.05), and transferrin (1.84 ± 0.12 vs. 2.32 ± 0.10, p < 0.05). These parameters correspond to first-degree malnutrition. There were direct correlations between anthropometric and biochemical parameters in the ALS group. BMI correlated with the blood levels of total protein (r = 0.22, p < 0.05), albumin (r = 0.27, p < 0.05), urea (r = 0.33, p < 0.05), creatinine (r = 0.30, p < 0.05), transferrin (r = 0.18, p < 0.05), and total lymphocyte count (r = 0.20, p < 0.05). PNI correlated with the blood levels of total protein (r = 0.53, p < 0.05), albumin (r = 0.87, p < 0.05), total cholesterol (r = 0.34, p < 0.05), transferrin (r = 0.40, p < 0.05), total lymphocyte count (r = 0.79, p < 0.05), urea (r = 0, 37, p < 0.05), and creatinine (r = 0.32, p < 0.05).

Conclusion

The study presents compelling evidence supporting the utilization of biochemical parameters, including total protein, albumin, urea, creatinine, transferrin, and total lymphocyte count, for potentially evaluating the nutritional status of individuals diagnosed with ALS.

Cumulative Genetic Score and C9orf72 Repeat Status Independently Contribute to Amyotrophic Lateral Sclerosis Risk in 2 Case-Control Studies

Background and Objectives

Most patients with amyotrophic lateral sclerosis (ALS) lack a monogenic mutation. This study evaluates ALS cumulative genetic risk in an independent Michigan and Spanish replication cohort using polygenic scores.

Methods

Participant samples from University of Michigan were genotyped and assayed for the chromosome 9 open reading frame 72 hexanucleotide expansion. Final cohort size was 219 ALS and 223 healthy controls after genotyping and participant filtering. Polygenic scores excluding the C9 region were generated using an independent ALS genome-wide association study (20,806 cases, 59,804 controls). Adjusted logistic regression and receiver operating characteristic curves evaluated the association and classification between polygenic scores and ALS status, respectively. Population attributable fractions and pathway analyses were conducted. An independent Spanish study sample (548 cases, 2,756 controls) was used for replication.

Results

Polygenic scores constructed from 275 single-nucleotide variation (SNV) had the best model fit in the Michigan cohort. An SD increase in ALS polygenic score associated with 1.28 (95% CI 1.04-1.57) times higher odds of ALS with area under the curve of 0.663 vs a model without the ALS polygenic score (p value = 1 × 10-6). The population attributable fraction of the highest 20th percentile of ALS polygenic scores, relative to the lowest 80th percentile, was 4.1% of ALS cases. Genes annotated to this polygenic score enriched for important ALS pathomechanisms. Meta-analysis with the Spanish study, using a harmonized 132 single nucleotide variation polygenic score, yielded similar logistic regression findings (odds ratio: 1.13, 95% CI 1.04-1.23).

Discussion

ALS polygenic scores can account for cumulative genetic risk in populations and reflect disease-relevant pathways. If further validated, this polygenic score will inform future ALS risk models.

Phenome-wide genetic-correlation analysis and genetically informed causal inference of amyotrophic lateral sclerosis

Leveraging genome-wide association statistics generated from a large study of amyotrophic lateral sclerosis (ALS; 29,612 cases and 122,656 controls) and UK Biobank (UKB; 4,024 phenotypes, up to 361,194 participants), we conducted a phenome-wide analysis of ALS genetic liability and identified 46 genetically correlated traits, such as fluid intelligence score (rg = - 0.21, p = 1.74 × 10-6), "spending time in pub or social club" (rg = 0.24, p = 2.77 × 10-6), non-work related walking (rg = - 0.25, p = 1.95 × 10-6), college education (rg = - 0.15, p = 7.08 × 10-5), "ever diagnosed with panic attacks (rg = 0.39, p = 4.24 × 10-5), and "self-reported other gastritis including duodenitis" (rg = 0.28, p = 1.4 × 10-3). To assess the putative directionality of these genetic correlations, we conducted a latent causal variable analysis, identifying significant genetic causality proportions (gĉp) linking ALS genetic liability to seven traits. While the genetic component of "self-reported other gastritis including duodenitis" showed a causal effect on ALS (gĉp = 0.50, p = 1.26 × 10-29), the genetic liability to ALS is potentially causal for multiple traits, also including an effect on "ever being diagnosed with panic attacks" (gĉp = 0.79, p = 5.011 × 10-15) and inverse effects on "other leisure/social group activities" (gĉp = 0.66, p = 1 × 10-4) and prospective memory result (gĉp = 0.35, p = 0.005). Our subsequent Mendelian randomization analysis indicated that some of these associations may be due to bidirectional effects. In conclusion, this phenome-wide investigation of ALS polygenic architecture highlights the widespread pleiotropy linking this disorder with several health domains.

Advances in sequencing technologies for amyotrophic lateral sclerosis research

Amyotrophic lateral sclerosis (ALS) is caused by upper and lower motor neuron loss and has a fairly rapid disease progression, leading to fatality in an average of 2-5 years after symptom onset. Numerous genes have been implicated in this disease; however, many cases remain unexplained. Several technologies are being used to identify regions of interest and investigate candidate genes. Initial approaches to detect ALS genes include, among others, linkage analysis, Sanger sequencing, and genome-wide association studies. More recently, next-generation sequencing methods, such as whole-exome and whole-genome sequencing, have been introduced. While those methods have been particularly useful in discovering new ALS-linked genes, methodological advances are becoming increasingly important, especially given the complex genetics of ALS. Novel sequencing technologies, like long-read sequencing, are beginning to be used to uncover the contribution of repeat expansions and other types of structural variation, which may help explain missing heritability in ALS. In this review, we discuss how popular and/or upcoming methods are being used to discover ALS genes, highlighting emerging long-read sequencing platforms and their role in aiding our understanding of this challenging disease.

Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program

While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV₁] and its ratio to forced vital capacity [FEV₁/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV₁ and FEV₁/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08-1.43] for PTRS versus 1.10 [0.96-1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p < 2.2 × 10^-16 with portability gains ranging from 5% to 28%) for both dichotomous COPD traits and across all smoking strata. Our study demonstrates the value of PTRS for improved cross-ethnic portability compared to PRS in predicting COPD risk.

Functional characterisation of the amyotrophic lateral sclerosis risk locus GPX3/TNIP1

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a complex, late-onset, neurodegenerative disease with a genetic contribution to disease liability. Genome-wide association studies (GWAS) have identified ten risk loci to date, including the TNIP1/GPX3 locus on chromosome five. Given association analysis data alone cannot determine the most plausible risk gene for this locus, we undertook a comprehensive suite of in silico, in vivo and in vitro studies to address this.

METHODS

The Functional Mapping and Annotation (FUMA) pipeline and five tools (conditional and joint analysis (GCTA-COJO), Stratified Linkage Disequilibrium Score Regression (S-LDSC), Polygenic Priority Scoring (PoPS), Summary-based Mendelian Randomisation (SMR-HEIDI) and transcriptome-wide association study (TWAS) analyses) were used to perform bioinformatic integration of GWAS data (Ncases = 20,806, Ncontrols = 59,804) with 'omics reference datasets including the blood (eQTLgen consortium N = 31,684) and brain (N = 2581). This was followed up by specific expression studies in ALS case-control cohorts (microarray Ntotal = 942, protein Ntotal = 300) and gene knockdown (KD) studies of human neuronal iPSC cells and zebrafish-morpholinos (MO).

RESULTS

SMR analyses implicated both TNIP1 and GPX3 (p < 1.15 × 10-6), but there was no simple SNP/expression relationship. Integrating multiple datasets using PoPS supported GPX3 but not TNIP1. In vivo expression analyses from blood in ALS cases identified that lower GPX3 expression correlated with a more progressed disease (ALS functional rating score, p = 5.5 × 10-3, adjusted R2 = 0.042, Beffect = 27.4 ± 13.3 ng/ml/ALSFRS unit) with microarray and protein data suggesting lower expression with risk allele (recessive model p = 0.06, p = 0.02 respectively). Validation in vivo indicated gpx3 KD caused significant motor deficits in zebrafish-MO (mean difference vs. control ± 95% CI, vs. control, swim distance = 112 ± 28 mm, time = 1.29 ± 0.59 s, speed = 32.0 ± 2.53 mm/s, respectively, p for all < 0.0001), which were rescued with gpx3 expression, with no phenotype identified with tnip1 KD or gpx3 overexpression.

CONCLUSIONS

These results support GPX3 as a lead ALS risk gene in this locus, with more data needed to confirm/reject a role for TNIP1. This has implications for understanding disease mechanisms (GPX3 acts in the same pathway as SOD1, a well-established ALS-associated gene) and identifying new therapeutic approaches. Few previous examples of in-depth investigations of risk loci in ALS exist and a similar approach could be applied to investigate future expected GWAS findings.

Genotoxic Damage During Brain Development Presages Prototypical Neurodegenerative Disease

Western Pacific Amyotrophic Lateral Sclerosis and Parkinsonism-Dementia Complex (ALS/PDC) is a disappearing prototypical neurodegenerative disorder (tau-dominated polyproteinopathy) linked with prior exposure to phytogenotoxins in cycad seed used for medicine and/or food. The principal cycad genotoxin, methylazoxymethanol (MAM), forms reactive carbon-centered ions that alkylate nucleic acids in fetal rodent brain and, depending on the timing of systemic administration, induces persistent developmental abnormalities of the cortex, hippocampus, cerebellum, and retina. Whereas administration of MAM prenatally or postnatally can produce animal models of epilepsy, schizophrenia or ataxia, administration to adult animals produces little effect on brain structure or function. The neurotoxic effects of MAM administered to rats during cortical brain development (specifically, gestation day 17) are used to model the histological, neurophysiological and behavioral deficits of human schizophrenia, a condition that may precede or follow clinical onset of motor neuron disease in subjects with sporadic ALS and ALS/PDC. While studies of migrants to and from communities impacted by ALS/PDC indicate the degenerative brain disorder may be acquired in juvenile and adult life, a proportion of indigenous cases shows neurodevelopmental aberrations in the cerebellum and retina consistent with MAM exposure in utero. MAM induces specific patterns of DNA damage and repair that associate with increased tau expression in primary rat neuronal cultures and with brain transcriptional changes that parallel those associated with human ALS and Alzheimer's disease. We examine MAM in relation to neurodevelopment, epigenetic modification, DNA damage/replicative stress, genomic instability, somatic mutation, cell-cycle reentry and cellular senescence. Since the majority of neurodegenerative disease lacks a solely inherited genetic basis, research is needed to explore the hypothesis that early-life exposure to genotoxic agents may trigger or promote molecular events that culminate in neurodegeneration.

A Comparison of Ten Polygenic Score Methods for Psychiatric Disorders Applied Across Multiple Cohorts

BACKGROUND

Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies. PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors.

METHODS

The Psychiatric Genomics Consortium Working Groups for schizophrenia and major depressive disorder bring together many independently collected case-control cohorts. We used these resources (31,328 schizophrenia cases, 41,191 controls; 248,750 major depressive disorder cases, 563,184 controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and 9 methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) were compared.

RESULTS

Compared with PC+T, the other 9 methods gave higher prediction statistics, MegaPRS, LDPred2, and SBayesR significantly so, explaining up to 9.2% variance in liability for schizophrenia across 30 target cohorts, an increase of 44%. For major depressive disorder across 26 target cohorts, these statistics were 3.5% and 59%, respectively.

CONCLUSIONS

Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparisons and are recommended in applications to psychiatric disorders.