Jessica Dennis

Parkinson’s disease (PD) is a disabling neurodegenerative disorder with a substantial heritable component. Despite major advances in genome-wide association studies (GWAS), polygenic risk scores (PRS) show reduced predictive performance outside European populations, limiting equitable translation. Latin American populations represent a particularly difficult case because of their characteristic three-way admixture. We evaluated the cross-ancestry transferability of PD PRS in 1,872 PD cases and 1,443 controls of Latin American ancestry using data from the Global Parkinson’s Genetics Program (GP2). PRS were constructed using summary statistics from a large European-ancestry GWAS, a moderately sized mixed-ancestry GWAS meta-analysis, and a small ancestry-matched Latin American GWAS. We benchmarked two single-ancestry approaches (PRSice-2 and SBayesRC) against two multi-ancestry methods (PRS-CSx and BridgePRS) that explicitly model cross-population genetic architecture. Across all performance metrics, SBayesRC performed best. PRS derived from large European GWAS achieved the highest effect size (odds ratio = 2.02; pseudo-R² = 0.031) while PRS derived from mixed ancestry GWAS meta-analysis yielded the highest discriminative ability (AUC=0.67). Our findings demonstrate that, under current sample size imbalances, well-powered European discovery GWAS outperform ancestry-matched but underpowered datasets in three-way admixed populations. Incorporating functional annotations, as implemented in SBayesRC, improves portability across ancestries. However, the full potential of multi-ancestry PRS methods will require substantially larger ancestry-matched discovery GWAS, underscoring the urgent need to expand genetic studies in underrepresented populations.

Eating disorders—including anorexia nervosa (AN), bulimia nervosa, and binge eating disorder—are clinically distinct but exhibit symptom overlap and diagnostic crossover. Genomic analyses have mostly examined AN. We conducted the first genomic meta-analysis of binge-eating behaviour (BE; 39,279 cases, 1,227,436 controls), alongside new analyses of AN (24,223 cases, 1,243,971 controls) and its subtypes (all European ancestries). We identified six loci associated with BE, including loci associated with higher body mass index (BMI) and impulse-control behaviours. AN GWAS yielded eight loci, validating six loci. Subsequent polygenic risk score analysis demonstrated an association with AN in two East Asian ancestry cohorts. BE and AN exhibited similar positive genetic correlations with psychiatric disorders, but opposing genetic correlations with anthropometric traits. Most of the genetic signal in BE and AN was not shared with BMI. We have extended eating disorder genomics beyond AN; future work will incorporate multiple diagnoses and global ancestries.

Both rare and common genetic variants contribute to human disease, and emerging evidence suggests that they combine additively to influence disease liability. However, the non-linear relationship between disease liability and disease prevalence means that risk variants may have more severe phenotypic consequences in high-risk polygenic backgrounds and minimal impact in low-risk backgrounds, resulting in uneven selection across the population. As a result, selection coefficients may be better modeled as distributions that differ across populations, time, environments, and individuals rather than single values. Further, the number of genes contributing to a trait and epistasis between alleles enhance negative selection due to the increased variance pushing more individuals to phenotypic extremes. Because disease-relevant phenotypes may be masked in certain genetic backgrounds, polygenic background should be considered when characterizing the molecular underpinnings of complex traits.

The HostSeq initiative recruited 10,059 Canadians infected with SARS-CoV-2 between March 2020 and March 2023, obtained clinical information on their disease experience and whole genome sequenced (WGS) their DNA. We analyzed the WGS data for genetic contributors to severe COVID-19 (considering 3,499 hospitalized cases and 4,975 non-hospitalized after quality control). We investigated the evidence for replication of loci reported by the International Host Genetics Initiative (HGI); analyzed the X chromosome; conducted rare variant gene-based analysis and polygenic risk score testing. Population stratification was adjusted for using meta-analysis across ancestry groups. We replicated two loci identified by the HGI for COVID-19 severity: the LZTFL1/SLC6A20 locus on chromosome 3 and the FOXP4 locus on chromosome 6 (the latter with a variant significant at P < 5E-8). We found novel significant associations with MRAS and WDR89 in gene-based analyses, and constructed a polygenic risk score that explained 1.01% of the variance in severe COVID-19. This study provides independent evidence confirming the robustness of previously identified COVID-19 severity loci by the HGI and identifies novel genes for further investigation.

Although Parkinson’s disease (PD) coincides with altered immune functioning, there are few reproducible associations between blood DNA methylation (DNAm) and PD case-control status. Integrative analyses of genotype and blood DNAm can address this gap and can help us characterize the biological function of PD genetic risk loci. First, we tested for associations between a PD genetic risk score (GRS) and DNAm. Our GRS included 36 independent genome-wide significant variants from the largest GWAS of PD to date. Our discovery sample was TERRE, consisting of French agricultural workers (71 PD cases and 147 controls). The GRS associated with DNAm at 85 CpG sites, with 19 associations replicated in an independent sample (DIG-PD). The majority of CpG sites (73) are within a 1.5 Mb window on chromosome 17, and 36 CpG sites annotate to MAPT and KANSL1 , neighboring genes that affect neurodegeneration. All associations were invariant to non-genetic factors, including exposure to commercial-grade pesticides, and omitting chromosome 17 variants from the GRS had little effect on association. Second, we compared our findings to the relationship between individual PD risk loci and blood DNAm using blood mQTL from a large independent meta-analysis (GoDMC). We found 79 CpG sites that colocalized with PD loci, and via summary Mendelian randomization analysis, we show 25/79 CpG sites where DNAm causally affects PD risk. The nine largest causal effects are within chromosome 17, including an effect within MAPT . Thus, all integrative analyses prioritized DNAm on chromosome 17, drawing from multiple independent data sets, meriting further study of this region.

Major depressive disorder (MDD) is a leading cause of morbidity and disability worldwide, with approximately twice as many women reported to have a lifetime occurrence of MDD than men. MDD is a polygenic trait, wherein hundreds to thousands of common genetic variants with small effect sizes contribute to risk of disease. This study investigated sex differences in the risk factor comorbidity and genetic architecture of MDD in over 16,000 people aged 45-85 from the Canadian Longitudinal Study on Aging (CLSA), with 21% of females (n=1,741) and 12% of males (n=1,055) coded with MDD. Polygenic risk scores (PRS) for individuals were made using sex-stratified and non-sex-specific (“both-sexes”) UK Biobank genome-wide association study summary statistics data. Odds of MDD for the sex-specific PRSs, socioeconomic, lifestyle and clinical risk factors associated with cardiovascular disease risk were assessed using a multivariable logistic regression model for each sex. Significant sex-specific risk factor associations with odds of MDD were found in females (history of ischemic heart disease (OR 1.52 (1.14-2.01), hypothyroidism (OR 1.42 (1.25-1.63), not being partnered (OR 1.34 (1.17-1.52)), having diabetes (OR 1.30 (1.11-1.52)), and higher female sex-specific autosomal PRS (OR 1.10 (1.04-1.16))) and males (high blood pressure, OR 1.35 (1.04-1.47)). Significant differences were observed in the proportion of variables that contributed to the most to each model, evaluated by relative pseudo-R ² values. Age contributed the most to the model for both sexes (46.9% for females, 32.5% for males), wherein younger age was associated with higher odds of MDD. These results underscore the relevance for sex-disaggregating analyses of complex traits, like MDD, and the incorporation of clinical variables into models of MDD, in applications such as early detection and primary prevention.

Summary: Molecular quantitative trait loci (QTL) allow us to understand the biology captured in genome-wide association studies (GWAS). The placenta regulates fetal development, and shows sex differences in DNA methylation. We therefore hypothesized that placental methylation QTL (mQTL) explains variation in genetic risk for childhood-onset traits, and does so differentially by sex. We analyzed 411 term placentas from two studies and found 49,252 methylation (CpG) sites with methylation QTL (mQTL) and 2,489 CpG sites with sex-dependent mQTL. All mQTL were enriched in regions active in prenatal tissues that typically affect gene expression. All mQTL were enriched in GWAS results for growth- and immune-related traits, but male- and female-specific mQTL were more enriched than cross-sex mQTL. mQTL colocalized with trait loci at 777 CpG sites, with 216 (28%) specific to males or females. Overall, mQTL specific to male and female placenta capture otherwise overlooked variation in childhood traits.

Objective: To identify risk factors and generate hypotheses for pediatric persistent postconcussion symptoms (PPCS). Setting: A regional healthcare system in the Southeastern United States. Participants: An electronic health record–based algorithm was developed and validated to identify PPCS cases and controls from an institutional database of more than 2.8 million patients. PPCS cases (n = 274) were patients aged 5 to 18 years with PPCS-related diagnostic codes or with PPCS key words identified by natural language processing of clinical notes. Age, sex, and year of index event–matched controls (n = 1096) were patients with mild traumatic brain injury codes only. Patients with moderate or severe traumatic brain injury were excluded. All patients used our healthcare system at least 3 times 180 days before their injury. Design: Case-control study. Main Measures: The outcome was algorithmic classification of PPCS. Exposures were all preinjury medical diagnoses assigned at least 180 days before the injury. Results: Cases and controls both had a mean of more than 9 years of healthcare system use preinjury. Of 221 preinjury medical diagnoses, headache disorder was associated with PPCS after accounting for multiple testing (odds ratio [OR] = 2.9; 95% confidence interval [CI]: 1.6-5.0; P = 2.1e-4). Six diagnoses were associated with PPCS at a suggestive threshold for statistical significance (false discovery rate P < .10): gastritis/duodenitis (OR = 2.8; 95% CI: 1.6-5.1; P = 5.0e-4), sleep disorders (OR = 2.3; 95% CI: 1.4-3.7; P = 7.4e-4), abdominal pain (OR = 1.6; 95% CI: 1.2-2.2; P = 9.2e-4), chronic sinusitis (OR = 2.8; 95% CI: 1.5-5.2; P = 1.3e-3), congenital anomalies of the skin (OR = 2.9; 95% CI: 1.5-5.5; P = 1.9e-3), and chronic pharyngitis/nasopharyngitis (OR = 2.4; 95% CI: 1.4-4.3; P = 2.5e-3). Conclusions: These results support the strong association of preinjury headache disorders with PPCS. An association of PPCS with prior gastritis/duodenitis, sinusitis, and pharyngitis/nasopharyngitis suggests a role for chronic inflammation in PPCS pathophysiology and risk, although results could equally be attributable to a higher likelihood of somatization among PPCS cases. Identified risk factors should be investigated further and potentially considered during the management of pediatric mild traumatic brain injury cases.

Objective: To identify risk factors and generate hypotheses for pediatric post-concussion syndrome (PCS) using a phenome-wide association study (PheWAS). Methods: A PheWAS (case-control) was conducted following the development and validation of a novel electronic health record-based algorithm that identified PCS cases and controls from an institutional database of >2.8 million patients. Cases were patients ages 5-18 with PCS codes or keywords identified by natural language processing of clinical notes. Controls were patients with mild traumatic brain injury (mTBI) codes only. Patients with moderate or severe brain injury were excluded. All patients used our healthcare system at least three times 180 days before their injury. Exposures included all pre-injury medical diagnoses assigned at least 180 days prior. Results: The algorithm identified 274 pediatric PCS cases (156 females) and 1,096 controls that were age and sex matched to cases. Cases and controls both had a mean of >8 years of healthcare system use pre-injury. Of 202 pre-injury medical, four were associated with PCS after controlling for multiple testing: headache disorders (OR=5.3; 95%CI 2.8-10.1; P= 3.8e-7), sleep disorders (OR=3.1; 95%CI 1.8-5.2; P= 2.6e-5), gastritis/duodenitis (OR=3.6, 95%CI 1.8-7.0; P= 2.1e-4), and chronic pharyngitis (OR=3.3; 95%CI 1.8-6.3; P= 2.2e-4). Conclusions: These results confirm the strong association of pre-injury headache disorders with PCS and provides evidence for the association of pre-injury sleep disorders with PCS. An association of PCS with prior chronic gastritis/duodenitis and pharyngitis was seen that suggests a role for chronic inflammation in PCS pathophysiology and risk. These factors should be considered during the management of pediatric mTBI cases.