Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum.

Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.

Plasma proteomic profiles of UK Biobank participants with multiple sclerosis.

OBJECTIVE: We aimed to describe plasma protein biomarkers of multiple sclerosis risk and to explore protein biomarkers of disease severity using radiological outcome measures. METHODS: Multiple sclerosis cases and controls were identified in UK Biobank, a longitudinal cohort study of ~500,000 British adults. Plasma proteins were assayed in ~50,000 UK Biobank participants using the Olink proximity extension assay. We performed case-control association testing to examine the association between 2911 proteins and multiple sclerosis, using linear models adjusted for confounding covariates. Associations with radiological lesion burden and brain volume were determined in a subset of the cohort with available magnetic resonance imaging, using normalized T2-hyperintensity volume or whole brain volume as the outcome measure. RESULTS: In total, 407 prevalent multiple sclerosis cases and 39,979 healthy controls were included. We discovered 72 proteins associated with multiple sclerosis at a Bonferroni-adjusted p value of 0.05, including established markers such as neurofilament light chain and glial fibrillary acidic protein. We observed a decrease in plasma Granzyme A, a marker of T cell and NK cell degranulation, which was specific to multiple sclerosis. Higher levels of plasma proteins involved in coagulation were associated with lower T2 lesion burden and preserved brain volume. INTERPRETATION: We report the largest plasma proteomic screen of multiple sclerosis, replicating important known associations and suggesting novel markers, such as the reduction in granzyme A. While these findings require external validation, they demonstrate the power of biobank-scale datasets for discovering new biomarkers for multiple sclerosis.

Modifiable risk factors for multiple sclerosis have consistent directions of effect across diverse ethnic backgrounds: a nested case-control study in an English population-based cohort.

BACKGROUND: Multiple sclerosis is a leading cause of non-traumatic neurological disability among young adults worldwide. Prior studies have identified modifiable risk factors for multiple sclerosis in cohorts of White ethnicity, such as infectious mononucleosis, smoking, and obesity during adolescence/early adulthood. It is unknown whether modifiable exposures for multiple sclerosis have a consistent impact on risk across ethnic groups. AIM: To determine whether modifiable risk factors for multiple sclerosis have similar effects across diverse ethnic backgrounds. METHODS: We conducted a nested case-control study using data from the UK Clinical Practice Research Datalink. Multiple sclerosis cases diagnosed from 2001 until 2022 were identified from electronic healthcare records and matched to unaffected controls based on year of birth. We used stratified logistic regression models and formal statistical interaction tests to determine whether the effect of modifiable risk factors for multiple sclerosis differed by ethnicity. RESULTS: We included 9662 multiple sclerosis cases and 118,914 age-matched controls. The cohort was ethnically diverse (MS: 277 South Asian [2.9%], 251 Black [2.6%]; Controls: 5043 South Asian [5.7%], 4019 Black [4.5%]). The age at MS diagnosis was earlier in the Black (40.5 [SD 10.9]) and Asian (37.2 [SD 10.0]) groups compared with White cohort (46.1 [SD 12.2]). There was a female predominance in all ethnic groups; however, the relative proportion of males was higher in the South Asian population (proportion of women 60.3% vs 71% [White] and 75.7% [Black]). Established modifiable risk factors for multiple sclerosis-smoking, obesity, infectious mononucleosis, low vitamin D, and head injury-were consistently associated with multiple sclerosis in the Black and South Asian cohorts. The magnitude and direction of these effects were broadly similar across all ethnic groups examined. There was no evidence of statistical interaction between ethnicity and any tested exposure, and no evidence to suggest that differences in area-level deprivation modifies these risk factor-disease associations. These findings were robust to a range of sensitivity analyses. CONCLUSIONS AND RELEVANCE: Established modifiable risk factors for multiple sclerosis are applicable across diverse ethnic backgrounds. Efforts to reduce the population incidence of multiple sclerosis by tackling these risk factors need to be inclusive of people from diverse ethnicities.

ADRA2A and IRX1 are putative risk genes for Raynaud's phenomenon.

Raynaud's phenomenon (RP) is a common vasospastic disorder that causes severe pain and ulcers, but despite its high reported heritability, no causal genes have been robustly identified. We conducted a genome-wide association study including 5,147 RP cases and 439,294 controls, based on diagnoses from electronic health records, and identified three unreported genomic regions associated with the risk of RP (p < 5 × 10-8). We prioritized ADRA2A (rs7090046, odds ratio (OR) per allele: 1.26; 95%-CI: 1.20-1.31; p < 9.6 × 10-27) and IRX1 (rs12653958, OR: 1.17; 95%-CI: 1.12-1.22, p < 4.8 × 10-13) as candidate causal genes through integration of gene expression in disease relevant tissues. We further identified a likely causal detrimental effect of low fasting glucose levels on RP risk (rG = -0.21; p-value = 2.3 × 10-3), and systematically highlighted drug repurposing opportunities, like the antidepressant mirtazapine. Our results provide the first robust evidence for a strong genetic contribution to RP and highlight a so far underrated role of α2A-adrenoreceptor signalling, encoded at ADRA2A, as a possible mechanism for hypersensitivity to catecholamine-induced vasospasms.

Genome-wide association study of thyroid-stimulating hormone highlights new genes, pathways and associations with thyroid disease.

Thyroid hormones play a critical role in regulation of multiple physiological functions and thyroid dysfunction is associated with substantial morbidity. Here, we use electronic health records to undertake a genome-wide association study of thyroid-stimulating hormone (TSH) levels, with a total sample size of 247,107. We identify 158 novel genetic associations, more than doubling the number of known associations with TSH, and implicate 112 putative causal genes, of which 76 are not previously implicated. A polygenic score for TSH is associated with TSH levels in African, South Asian, East Asian, Middle Eastern and admixed American ancestries, and associated with hypothyroidism and other thyroid disease in South Asians. In Europeans, the TSH polygenic score is associated with thyroid disease, including thyroid cancer and age-of-onset of hypothyroidism and hyperthyroidism. We develop pathway-specific genetic risk scores for TSH levels and use these in phenome-wide association studies to identify potential consequences of pathway perturbation. Together, these findings demonstrate the potential utility of genetic associations to inform future therapeutics and risk prediction for thyroid diseases.

Influence of autozygosity on common disease risk across the phenotypic spectrum.

Autozygosity is associated with rare Mendelian disorders and clinically relevant quantitative traits. We investigated associations between the fraction of the genome in runs of homozygosity (FROH) and common diseases in Genes & Health (n = 23,978 British South Asians), UK Biobank (n = 397,184), and 23andMe. We show that restricting analysis to offspring of first cousins is an effective way of reducing confounding due to social/environmental correlates of FROH. Within this group in G&H+UK Biobank, we found experiment-wide significant associations between FROH and twelve common diseases. We replicated associations with type 2 diabetes (T2D) and post-traumatic stress disorder via within-sibling analysis in 23andMe (median n = 480,282). We estimated that autozygosity due to consanguinity accounts for 5%-18% of T2D cases among British Pakistanis. Our work highlights the possibility of widespread non-additive genetic effects on common diseases and has important implications for global populations with high rates of consanguinity.

ADAMS project: a genetic Association study in individuals from Diverse Ancestral backgrounds with Multiple Sclerosis based in the UK.

PURPOSE: Genetic studies of multiple sclerosis (MS) susceptibility and severity have focused on populations of European ancestry. Studying MS genetics in other ancestral groups is necessary to determine the generalisability of these findings. The genetic Association study in individuals from Diverse Ancestral backgrounds with Multiple Sclerosis (ADAMS) project aims to gather genetic and phenotypic data on a large cohort of ancestrally-diverse individuals with MS living in the UK. PARTICIPANTS: Adults with self-reported MS from diverse ancestral backgrounds. Recruitment is via clinical sites, online (https://app.mantal.co.uk/adams) or the UK MS Register. We are collecting demographic and phenotypic data using a baseline questionnaire and subsequent healthcare record linkage. We are collecting DNA from participants using saliva kits (Oragene-600) and genotyping using the Illumina Global Screening Array V.3. FINDINGS TO DATE: As of 3 January 2023, we have recruited 682 participants (n=446 online, n=55 via sites, n=181 via the UK MS Register). Of this initial cohort, 71.2% of participants are female, with a median age of 44.9 years at recruitment. Over 60% of the cohort are non-white British, with 23.5% identifying as Asian or Asian British, 16.2% as Black, African, Caribbean or Black British and 20.9% identifying as having mixed or other backgrounds. The median age at first symptom is 28 years, and median age at diagnosis is 32 years. 76.8% have relapsing-remitting MS, and 13.5% have secondary progressive MS. FUTURE PLANS: Recruitment will continue over the next 10 years. Genotyping and genetic data quality control are ongoing. Within the next 3 years, we aim to perform initial genetic analyses of susceptibility and severity with a view to replicating the findings from European-ancestry studies. In the long term, genetic data will be combined with other datasets to further cross-ancestry genetic discoveries.

Early depressive symptoms and disability accrual in Multiple Sclerosis: a UK MS Register study.

Understanding the associations and potential drivers of long-term disability in Multiple Sclerosis (MS) is of clinical and prognostic value. Previous data have suggested a link between depression and disability accrual in MS. We aimed to determine whether depression in early MS predicts subsequent accrual of disability. Using data from the UK MS Register, we identified individuals with and without symptoms of depression and anxiety close to disease onset. We used Cox proportional hazards regression to evaluate whether early depressive or anxiety symptoms predict subsequent physical disability worsening, measured using the Expanded Disability Status Scale (EDSS). We analysed data from 862 people with MS of whom 134 (15.5%) reached an EDSS of ≥ 6.0. Early depressive symptoms were associated with an increased risk of reaching an EDSS of 6.0 (HR 2.42, 95% CI 1.49-3.95, p < 0.001), however this effect dissipated when adjusting for baseline EDSS (HR 1.40, 95% CI 0.84-2.32, p = 0.2). These data suggest that early depressive symptoms in MS are associated with subsequent disability accrual, but are likely the result of disability rather than its cause.

Polygenic risk score prediction of multiple sclerosis in individuals of South Asian ancestry.

Polygenic risk scores aggregate an individual's burden of risk alleles to estimate the overall genetic risk for a specific trait or disease. Polygenic risk scores derived from genome-wide association studies of European populations perform poorly for other ancestral groups. Given the potential for future clinical utility, underperformance of polygenic risk scores in South Asian populations has the potential to reinforce health inequalities. To determine whether European-derived polygenic risk scores underperform at multiple sclerosis prediction in a South Asian-ancestry population compared with a European-ancestry cohort, we used data from two longitudinal genetic cohort studies: Genes & Health (2015-present), a study of ∼50 000 British-Bangladeshi and British-Pakistani individuals, and UK Biobank (2006-present), which is comprised of ∼500 000 predominantly White British individuals. We compared individuals with and without multiple sclerosis in both studies (Genes & Health: N Cases = 42, N Control = 40 490; UK Biobank: N Cases = 2091, N Control = 374 866). Polygenic risk scores were calculated using clumping and thresholding with risk allele effect sizes obtained from the largest multiple sclerosis genome-wide association study to date. Scores were calculated with and without the major histocompatibility complex region, the most influential locus in determining multiple sclerosis risk. Polygenic risk score prediction was evaluated using Nagelkerke's pseudo-R 2 metric adjusted for case ascertainment, age, sex and the first four genetic principal components. We found that, as expected, European-derived polygenic risk scores perform poorly in the Genes & Health cohort, explaining 1.1% (including the major histocompatibility complex) and 1.5% (excluding the major histocompatibility complex) of disease risk. In contrast, multiple sclerosis polygenic risk scores explained 4.8% (including the major histocompatibility complex) and 2.8% (excluding the major histocompatibility complex) of disease risk in European-ancestry UK Biobank participants. These findings suggest that polygenic risk score prediction of multiple sclerosis based on European genome-wide association study results is less accurate in a South Asian population. Genetic studies of ancestrally diverse populations are required to ensure that polygenic risk scores can be useful across ancestries.

Association Between Antiepileptic Drugs and Incident Parkinson Disease.

Importance: Recent studies have highlighted an association between epilepsy and Parkinson disease (PD). The role of antiepileptic drugs (AEDs) has not been explored. Objective: To investigate the association between AEDs and incident PD. Design, Setting, and Participants: This nested case-control study started collecting data from the UK Biobank (UKB) in 2006, and data were extracted on June 30, 2021. Individuals with linked primary care prescription data were included. Cases were defined as individuals with a Hospital Episode Statistics (HES)-coded diagnosis of PD. Controls were matched 6:1 for age, sex, race and ethnicity, and socioeconomic status. Prescription records were searched for AEDs prescribed prior to diagnosis of PD. The UKB is a longitudinal cohort study with more than 500 000 participants; 45% of individuals in the UKB have linked primary care prescription data. Participants living in the UK aged between 40 and 69 years were recruited to the UKB between 2006 and 2010. All participants with UKB-linked primary care prescription data (n = 222 106) were eligible for enrollment in the study. Individuals with only a self-reported PD diagnosis or missing data for the matching variables were excluded. In total, 1477 individuals were excluded; 49 were excluded due to having only self-reported PD, and 1428 were excluded due to missing data. Exposures: Exposure to AEDs (carbamazepine, lamotrigine, levetiracetam, and sodium valproate) was defined using routinely collected prescription data derived from primary care. Main Outcomes and Measures: Odds ratios and 95% CIs were calculated using adjusted logistic regression models for individuals prescribed AEDs before the first date of HES-coded diagnosis of PD. Results: In this case-control study, there were 1433 individuals with an HES-coded PD diagnosis (cases) and 8598 controls in the analysis. Of the 1433 individuals, 873 (60.9%) were male, 1397 (97.5%) had their race and ethnicity recorded as White, and their median age was 71 years (IQR, 65-75 years). An association was found between AED prescriptions and incident PD (odds ratio, 1.80; 95% CI, 1.35-2.40). There was a trend for a greater number of prescription issues and multiple AEDs being associated with a greater risk of PD. Conclusions and Relevance: This study, the first to systematically look at PD risk in individuals prescribed the most common AEDs, to our knowledge, found evidence of an association between AEDs and incident PD. With the recent literature demonstrating an association between epilepsy and PD, this study provides further insights.

No evidence for an association between alcohol consumption and Multiple Sclerosis risk: a UK Biobank study.

Multiple Sclerosis (MS) has been linked to a variety of environmental risk factors, including smoking, Epstein-Barr Virus infection, and childhood obesity. There is some evidence to support a relationship between alcohol consumption and MS risk, but this finding has been inconsistent across cohorts. A protective link between alcohol consumption and MS risk is seen in Swedish and Danish cohorts, however evidence from other cohorts and mendelian randomisation studies have failed to support this relationship. We assessed the relationship between alcohol consumption (never vs. ever drinking) and MS in 409,228 individuals (2100 with MS) from UK Biobank (UKB). We used multivariable logistic regression models adjusted for age and sex. To determine whether there was evidence of statistical interaction between alcohol consumption and HLA-DRB1*15:01 genotype, we calculated interaction on the additive and multiplicative scales. We analysed data from 2100 individuals with MS (72.3% female, median age at recruitment 56) and 407,128 controls (53.9% female, median age at recruitment 58). We found no evidence for an association between alcohol consumption and MS risk (OR = 1.12, 95% CI 0.61-2.08, p = 0.314). As expected, the HLA-DRB1*15:01 allele was strongly associated with MS risk (OR = 2.72, 95% CI 2.72-2.72, p < 2 × 10-16). We found no evidence of statistical interaction between non-drinking and MS risk on either the multiplicative scale (p = 0.8) or on the additive scale (Attributable Proportion = 0.03, 95% CI - 0.43-0.29, P = 0.45). Empirical power calculations indicated reasonable statistical power (85%) to detect a protective effect of alcohol consumption of Relative Risk ≤ 0.7. We were thus unable to replicate findings from other cohorts within UK Biobank. The inconsistent association seen between studies may reflect limited statistical power to detect a weak effect, differences in population characteristics, or the lack of a true causal association.

The shared genetic architecture of modifiable risk for Alzheimer's disease: a genomic structural equation modelling study.

Targeting modifiable risk factors may help to prevent Alzheimer's disease (AD), but the pathways by which these risk factors influence AD risk remain incompletely understood. We identified genome-wide association studies for AD and its major modifiable risk factors. We calculated the genetic correlation among these traits and modelled this using genomic structural equation modelling. We identified complex networks of genetic overlap among AD risk factors, but AD itself was largely genetically distinct. The data were best explained by a bi-factor model, incorporating a Common Factor for AD risk, and 3 orthogonal sub-clusters of risk factors. Taken together, our findings suggest that there is extensive shared genetic architecture between AD modifiable risk factors, but this is largely independent of AD genetic pathways. Extensive genetic pleiotropy between risk factors may influence AD indirectly by decreasing cognitive reserve or increasing risk of multimorbidity, leading to poorer brain health. Further work to understand the biology reflected by this communality may provide novel mechanistic insights that could help to prioritise targets for dementia prevention.

Age-specific effects of childhood body mass index on multiple sclerosis risk.

OBJECTIVE: Higher body mass index (BMI) during early life is thought to be a causal risk factor for multiple sclerosis (MS). We used longitudinal Mendelian randomisation (MR) to determine whether there is a critical window during which BMI influences MS risk. METHODS: Summary statistics for childhood BMI (n ~ 28,000 children) and for MS susceptibility were obtained from recent large genome-wide association studies (GWAS) (n = 14,802 MS, 26,703 controls). We generated exposure instruments for BMI during four non-overlapping age epochs (< 3 months, 3 months-1.5 years, 2-5 years, and 7-8 years) and performed MR using the inverse variance weighted method with standard sensitivity analyses. Multivariable MR was used to account for effects mediated via later-life BMI. RESULTS: For all age epochs other than birth, genetically determined higher BMI was associated with an increased liability to MS: Birth [Odds Ratio (OR) 0.81, 95% Confidence Interval (CI) 0.50-1.31, Number of Single-Nucleotide Polymorphisms (NSNPs) = 7, p = 0.39], Infancy (OR 1.18, 95% CI 1.04-1.33, NSNPs = 18, p = 0.01), Early childhood (OR 1.31, 95% CI 1.03-1.66, NSNPs = 4, p = 0.03), Later childhood (OR 1.34, 95% CI 1.08-1.66, NSNPs = 4, p = 0.01). Multivariable MR suggested that these effects may be mediated by effects on adult BMI. CONCLUSION: We provide evidence using MR that genetically determined higher BMI during early life is associated with increased MS risk. This effect may be driven by shared genetic architecture with later-life BMI.

Polygenic Resilience Modulates the Penetrance of Parkinson Disease Genetic Risk Factors.

OBJECTIVE: The aim of the current study is to understand why some individuals avoid developing Parkinson disease (PD) despite being at relatively high genetic risk, using the largest datasets of individual-level genetic data available. METHODS: We calculated polygenic risk score to identify controls and matched PD cases with the highest burden of genetic risk for PD in the discovery cohort (International Parkinson's Disease Genomics Consortium, 7,204 PD cases and 9,412 controls) and validation cohorts (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease, 8,968 cases and 7,598 controls; UK Biobank, 2,639 PD cases and 14,301 controls; Accelerating Medicines Partnership-Parkinson's Disease Initiative, 2,248 cases and 2,817 controls). A genome-wide association study meta-analysis was performed on these individuals to understand genetic variation associated with resistance to disease. We further constructed a polygenic resilience score, and performed multimarker analysis of genomic annotation (MAGMA) gene-based analyses and functional enrichment analyses. RESULTS: A higher polygenic resilience score was associated with a lower risk for PD (ß = -0.054, standard error [SE] = 0.022, p = 0.013). Although no single locus reached genome-wide significance, MAGMA gene-based analyses nominated TBCA as a putative gene. Furthermore, we estimated the narrow-sense heritability associated with resilience to PD (h2  = 0.081, SE = 0.035, p = 0.0003). Subsequent functional enrichment analysis highlighted histone methylation as a potential pathway harboring resilience alleles that could mitigate the effects of PD risk loci. INTERPRETATION: The present study represents a novel and comprehensive assessment of heritable genetic variation contributing to PD resistance. We show that a genetic resilience score can modify the penetrance of PD genetic risk factors and therefore protect individuals carrying a high-risk genetic burden from developing PD. ANN NEUROL 2022;92:270-278.

Orexin 1 Receptor Antagonism in the Basolateral Amygdala Shifts the Balance From Pro- to Antistress Signaling and Behavior.

BACKGROUND: Stress produces differential behavioral responses through select molecular modifications to specific neurocircuitry elements. The orexin (Orx) system targets key components of this neurocircuitry in the basolateral amygdala (BLA). METHODS: We assessed the contribution of intra-BLA Orx1 receptors (Orx1Rs) in the expression of stress-induced phenotypes of mice. Using the Stress Alternatives Model, a social stress paradigm that produces two behavioral phenotypes, we characterized the role of intra-BLA Orx1R using acute pharmacological inhibition (SB-674042) and genetic knockdown (AAV-U6-Orx1R-shRNA) strategies. RESULTS: In the BLA, we observed that Orx1R (Hcrtr1) messenger RNA is predominantly expressed in CamKIIα+ glutamatergic neurons and rarely in GABAergic (gamma-aminobutyric acidergic) cells. While there is a slight overlap in Hcrtr1 and Orx2 receptor (Hcrtr2) messenger RNA expression in the BLA, we find that these receptors are most often expressed in separate cells. Antagonism of intra-BLA Orx1R after phenotype formation shifted behavioral expression from stress-sensitive (Stay) to stress-resilient (Escape) responses, an effect that was mimicked by genetic knockdown. Acute inhibition of Orx1R in the BLA also reduced contextual and cued fear freezing responses in Stay animals. This phenotype-specific behavioral change was accompanied by biased molecular transcription favoring Hcrtr2 over Hcrtr1 and Mapk3 over Plcb1 cell signaling cascades and enhanced Bdnf messenger RNA. CONCLUSIONS: Functional reorganization of intra-BLA gene expression is produced by antagonism of Orx1R, which promotes elevated Hcrtr2, greater Mapk3, and increased Bdnf expression. Together, these results provide evidence for a receptor-driven mechanism that balances pro- and antistress responses within the BLA.

Assessment of Risk Factors and Early Presentations of Parkinson Disease in Primary Care in a Diverse UK Population.

IMPORTANCE: Early features of Parkinson disease (PD) have been described through population-based studies that overrepresent White, affluent groups and may not be generalizable. OBJECTIVE: To investigate the association between risk factors and prediagnostic presentations of PD in an ethnically diverse UK population with high socioeconomic deprivation but universal access to health care. DESIGN, SETTING, AND PARTICIPANTS: A nested case-control study was conducted using electronic health care records on 1 016 277 individuals from primary care practices in East London to extract clinical information recorded between 1990 and February 6, 2018. The data were analyzed between September 3, 2020, and September 3, 2021. Individuals with a diagnosis of PD were compared with controls without PD or other major neurological conditions. MAIN OUTCOMES AND MEASURES: A matched analysis (10 controls matched for each patient with PD according to age and sex) and an unmatched analysis (adjusted for age and sex) were undertaken using multivariable logistic regression to determine associations between risk factors and prediagnostic presentations to primary care with subsequent diagnosis of PD. Three time periods (<2, 2-<5, and 5-10 years before diagnosis) were analyzed separately and together. RESULTS: Of 1 016 277 individuals included in the data set, 5699 were excluded and 1055 patients with PD and 1 009 523 controls were included in the analysis. Patients with PD were older than controls (mean [SD], 72.9 [11.3] vs 40.3 [15.2] years), and more were male (632 [59.9%] vs 516 862 [51.2%]). In the matched analysis (1055 individuals with PD and 10 550 controls), associations were found for tremor (odds ratio [OR], 145.96; 95% CI, 90.55-235.28) and memory symptoms (OR, 8.60; 95% CI, 5.91-12.49) less than 2 years before the PD diagnosis. The associations were also found up to 10 years before PD diagnosis for tremor and 5 years for memory symptoms. Among midlife risk factors, hypertension (OR, 1.36; 95% CI, 1.19-1.55) and type 2 diabetes (OR, 1.39; 95% CI, 1.19-1.62) were associated with subsequent diagnosis of PD. Associations with early nonmotor features, including hypotension (OR, 6.84; 95% CI, 3.38-13.85), constipation (OR, 3.29; 95% CI, 2.32-4.66), and depression (OR, 4.69; 95% CI, 2.88-7.63), were also noted. Associations were found for epilepsy (OR, 2.5; 95% CI, 1.63-3.83) and hearing loss (OR, 1.66; 95% CI, 1.06-2.58), which have not previously been well reported. These findings were replicated using data from the UK Biobank. No association with future PD diagnosis was found for ethnicity or deprivation index level. CONCLUSIONS AND RELEVANCE: This study provides data suggesting that a range of comorbidities and symptoms are encountered in primary care settings before PD diagnosis in an ethnically diverse and deprived population. Novel temporal associations were observed for epilepsy and hearing loss with subsequent development of PD. The prominence of memory symptoms suggests an excess of cognitive dysfunction in early PD in this population or difficulty in correctly ascertaining symptoms in traditionally underrepresented groups.

Type 2 Diabetes as a Determinant of Parkinson's Disease Risk and Progression.

BACKGROUND: Type 2 diabetes (T2DM) and Parkinson's disease (PD) are prevalent diseases that affect an aging population. Previous systematic reviews and meta-analyses have explored the relationship between diabetes and the risk of PD, but the results have been conflicting. OBJECTIVE: The objective was to investigate T2DM as a determinant of PD through a meta-analysis of observational and genetic summary data. METHODS: A systematic review and meta-analysis of observational studies was undertaken by searching 6 databases. We selected the highest-quality studies investigating the association of T2DM with PD risk and progression. We then used Mendelian randomization (MR) to investigate the causal effects of genetic liability toward T2DM on PD risk and progression, using summary data derived from genome-wide association studies. RESULTS: In the observational part of the study, pooled effect estimates showed that T2DM was associated with an increased risk of PD (odds ratio [OR] 1.21, 95% confidence interval [CI] 1.07-1.36), and there was some evidence that T2DM was associated with faster progression of motor symptoms (standardized mean difference [SMD] 0.55, 95% CI 0.39-0.72) and cognitive decline (SMD -0.92, 95% CI -1.50 to -0.34). Using MR, we found supportive evidence for a causal effect of diabetes on PD risk (inverse-variance weighted method [IVW] OR 1.08, 95% CI 1.02-1.14; P = 0.010) and some evidence of an effect on motor progression (IVW OR 1.10, 95% CI 1.01-1.20; P = 0.032) but not on cognitive progression. CONCLUSIONS: Using meta-analyses of traditional observational studies and genetic data, we observed convincing evidence for an effect of T2DM on PD risk and new evidence to support a role in PD progression. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Summary-data-based Mendelian randomization prioritizes potential druggable targets for multiple sclerosis.

Multiple sclerosis is a complex autoimmune disease caused by a combination of genetic and environmental factors. Translation of Genome-Wide Association Study findings into therapeutics and effective preventive strategies has been limited to date. We used summary-data-based Mendelian randomization to synthesize findings from public expression quantitative trait locus, methylation quantitative trait locus and Multiple Sclerosis Genome-Wide Association Study datasets. By correlating the effects of methylation on multiple sclerosis, methylation on expression and expression on multiple sclerosis susceptibility, we prioritize genetic loci with evidence of influencing multiple sclerosis susceptibility. We overlay these findings onto a list of 'druggable' genes, i.e. genes which are currently, or could theoretically, be targeted by therapeutic compounds. We use GeNets and search tool for the retrieval of interacting genes/proteins to identify protein-protein interactions and druggable pathways enriched in our results. We extend these findings to a model of Epstein-Barr virus-infected B cells, lymphoblastoid cell lines. We conducted a systematic review of prioritized genes using the Open Targets platform to identify completed and planned trials targeting prioritized genes in multiple sclerosis and related disease areas. Expression of 45 genes in peripheral blood was strongly associated with multiple sclerosis susceptibility (False discovery rate 0.05). Of these 45 genes, 20 encode a protein which is currently targeted by an existing therapeutic compound. These genes were enriched for Gene Ontology terms pertaining to immune system function and leucocyte signalling. We refined this prioritized gene list by restricting to loci where CpG site methylation was associated with multiple sclerosis susceptibility, with gene expression and where expression was associated with multiple sclerosis susceptibility. This approach yielded a list of 15 prioritized druggable target genes for which there was evidence of a pathway linking methylation, expression and multiple sclerosis. Five of these 15 genes are targeted by existing drugs and three were replicated in a smaller expression Quantitative Trait Loci dataset (CD40, MERTK and PARP1). In lymphoblastoid cell lines, this approach prioritized 7 druggable gene targets, of which only one was prioritized by the multi-omic approach in peripheral blood (FCRL3). Systematic review of Open Targets revealed multiple early-phase trials targeting 13/20 prioritized genes in disorders related to multiple sclerosis. We use public datasets and summary-data-based Mendelian randomization to identify a list of prioritized druggable genetic targets in multiple sclerosis. We hope our findings could be translated into a platform for developing targeted preventive therapies.