Promoting equity in clinical research: The role of social determinants of health.

OBJECTIVE: This study aims to investigate the association between social determinants of health (SDoH) and clinical research recruitment outcomes and recommends evidence-based strategies to enhance equity. MATERIALS AND METHODS: Data were collected from the internal clinical study manager database, clinical data warehouse, and clinical research registry. Study characteristics (e.g., study phase) and sociodemographic information were extracted. Median neighborhood income, distance from the study location, and Area Deprivation Index (ADI) were calculated. Mixed effect generalized regression was used for clustering effects and false discovery rate adjustment for multiple testing. A stratified analysis was performed to examine the impact in distinct medical departments. RESULTS: The study sample consisted of 3,962 individuals, with a mean age of 61.5 years, 53.6 % male, 54.2 % White, and 49.1 % non-Hispanic or Latino. Study characteristics revealed a variety of protocols across different departments, with cardiology having the highest percentage of participants (46.4 %). Industry funding was the most common (74.5 %), and digital advertising and personal outreach were the main recruitment methods (58.9 % and 90.8 %). DISCUSSION: The analysis demonstrated significant associations between participant characteristics and research participation, including biological sex, age, ethnicity, and language. The stratified analysis revealed other significant associations for recruitment strategies. SDoH is crucial to clinical research recruitment, and this study presents evidence-based solutions for equity and inclusivity. Researchers can tailor recruitment strategies to overcome barriers and increase participant diversity by identifying participant characteristics and research involvement status. CONCLUSION: The findings highlight the relevance of clinical research inequities and equitable representation of historically underrepresented populations. We need to improve recruitment strategies to promote diversity and inclusivity in research.

ATN cerebrospinal fluid biomarkers in dementia with Lewy bodies: Initial results from the United States Dementia with Lewy Bodies Consortium.

INTRODUCTION: The National Institute on Aging - Alzheimer's Association (NIA-AA) ATN research framework proposes to use biomarkers for amyloid (A), tau (T), and neurodegeneration (N) to stage individuals with AD pathological features and track changes longitudinally. The overall aim was to utilize this framework to characterize pre-mortem ATN status longitudinally in a clinically diagnosed cohort of dementia with Lewy bodies (DLB) and to correlate it with the post mortem diagnosis. METHODS: The cohort was subtyped by cerebrospinal fluid (CSF) ATN category. A subcohort had longitudinal data, and a subgroup was neuropathologically evaluated. RESULTS: We observed a significant difference in Aß42/40 after 12 months in the A+T- group. Post mortem neuropathologic analyses indicated that most of the p-Tau 181 positive (T+) cases also had a high Braak stage. DISCUSSION: This suggests that DLB patients who are A+ but T- may need to be monitored to determine whether they remain A+ or ever progress to T positivity. HIGHLIGHTS: Some A+T- DLB subjects transition from A+ to negative after 12-months. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Monitoring of the A+T- sub-type of DLB may be necessary.

Providing genetic testing and genetic counseling for Parkinson's disease to the community.

PURPOSE: To evaluate the feasibility and impact of offering genetic testing and counseling to patients with Parkinson's disease (PD), with the potential to enroll in gene-targeted clinical trials and improve clinical care. METHODS: A multicenter, exploratory pilot study at 7 academic hospital sites in the United States tracked enrollment and randomized participants to receive results and genetic counseling at local sites or by genetic counselors, remotely. Follow-up surveys measured participant/provider satisfaction, knowledge, and psychological impact. RESULTS: From September 5, 2019 to January 4, 2021, 620 participants were enrolled and 387 completed outcome surveys. There were no significant differences in outcomes between local and remote sites, with both arms reporting high knowledge and satisfaction scores (>80%). Notably, 16% of those tested had reportable PD gene variants (pathogenic/likely pathogenic/risk allele). CONCLUSION: Local clinicians, as well as genetic counselors, with educational support as needed, can effectively return genetic results for PD as we observed favorable outcome measures in both groups. Increasing access to PD genetic testing and counseling is urgent; this can inform future efforts to integrate genetic testing and counseling into clinical care for all those with PD.

Parkinson Disease and Subthalamic Nucleus Deep Brain Stimulation: Cognitive Effects in GBA Mutation Carriers.

OBJECTIVE: This study was undertaken to compare the rate of change in cognition between glucocerebrosidase (GBA) mutation carriers and noncarriers with and without subthalamic nucleus deep brain stimulation (STN-DBS) in Parkinson disease. METHODS: Clinical and genetic data from 12 datasets were examined. Global cognition was assessed using the Mattis Dementia Rating Scale (MDRS). Subjects were examined for mutations in GBA and categorized as GBA carriers with or without DBS (GBA+DBS+, GBA+DBS-), and noncarriers with or without DBS (GBA-DBS+, GBA-DBS-). GBA mutation carriers were subcategorized according to mutation severity (risk variant, mild, severe). Linear mixed modeling was used to compare rate of change in MDRS scores over time among the groups according to GBA and DBS status and then according to GBA severity and DBS status. RESULTS: Data were available for 366 subjects (58 GBA+DBS+, 82 GBA+DBS-, 98 GBA-DBS+, and 128 GBA-DBS- subjects), who were longitudinally followed (range = 36-60 months after surgery). Using the MDRS, GBA+DBS+ subjects declined on average 2.02 points/yr more than GBA-DBS- subjects (95% confidence interval [CI] = -2.35 to -1.69), 1.71 points/yr more than GBA+DBS- subjects (95% CI = -2.14 to -1.28), and 1.49 points/yr more than GBA-DBS+ subjects (95% CI = -1.80 to -1.18). INTERPRETATION: Although not randomized, this composite analysis suggests that the combined effects of GBA mutations and STN-DBS negatively impact cognition. We advise that DBS candidates be screened for GBA mutations as part of the presurgical decision-making process. We advise that GBA mutation carriers be counseled regarding potential risks associated with STN-DBS so that alternative options may be considered. ANN NEUROL 2022;91:424-435.

Patterns of TDP-43 Deposition in Brains with LRRK2 G2019S Mutations.

OBJECTIVE: To assess for TDP-43 deposits in brains with and without a LRRK2 G2019S mutation. BACKGROUND: LRRK2 G2019S mutations have been associated with parkinsonism and a wide range of pathological findings. There are no systematic studies examining the frequency and extent of TDP-43 deposits in neuropathological samples from LRRK2 G2019S carriers. METHODS: Twelve brains with LRRK2 G2019S mutations were available for study from the New York Brain Bank at Columbia University; 11 of them had samples available for TDP-43 immunostaining. Clinical, demographic, and pathological data are reported for 11 brains with a LRRK2 G2019S mutation and compared to 11 brains without GBA1 or LRRK2 G2019S mutations with a pathologic diagnosis of Parkinson's disease (PD) or diffuse Lewy body disease. They were frequency matched by age, gender, parkinsonism age of onset, and disease duration. RESULTS: TDP-43 aggregates were present in 73% (n = 8) of brains with a LRRK2 mutation and 18% (n = 2) of brains without a LRRK2 mutation (P = 0.03). In one brain with a LRRK2 mutation, TDP-43 proteinopathy was the primary neuropathological change. CONCLUSIONS: Extranuclear TDP-43 aggregates are observed with greater frequency in LRRK2 G2019S autopsies compared to PD cases without a LRRK2 G2019S mutation. The association between LRRK2 and TDP-43 should be further explored. © 2023 International Parkinson and Movement Disorder Society.

International Genetic Testing and Counseling Practices for Parkinson's Disease.

BACKGROUND: There is growing clinical and research utilization of genetic testing in Parkinson's disease (PD), including direct-to-consumer testing. OBJECTIVES: The aim is to determine the international landscape of genetic testing in PD to inform future worldwide recommendations. METHODS: A web-based survey assessing current practices, concerns, and barriers to genetic testing and counseling was administered to the International Parkinson and Movement Disorders Society membership. RESULTS: Common hurdles across sites included cost and access to genetic testing, and counseling, as well as education on genetic counseling. Region-dependent differences in access to and availability of testing and counseling were most notable in Africa. High-income countries also demonstrated heterogeneity, with European nations more likely to have genetic testing covered through insurance than Pan-American and Asian countries. CONCLUSIONS: This survey highlights not only diversity of barriers in different regions but also the shared and highly actionable needs for improved education and access to genetic counseling and testing for PD worldwide. © 2023 International Parkinson and Movement Disorder Society.

Genetic Testing in Parkinson's Disease.

Genetic testing for persons with Parkinson's disease is becoming increasingly common. Significant gains have been made regarding genetic testing methods, and testing is becoming more readily available in clinical, research, and direct-to-consumer settings. Although the potential utility of clinical testing is expanding, there are currently no proven gene-targeted therapies, but clinical trials are underway. Furthermore, genetic testing practices vary widely, as do knowledge and attitudes of relevant stakeholders. The specter of testing mandates financial, ethical, and physician engagement, and there is a need for guidelines to help navigate the myriad of challenges. However, to develop guidelines, gaps and controversies need to be clearly identified and analyzed. To this end, we first reviewed recent literature and subsequently identified gaps and controversies, some of which were partially addressed in the literature, but many of which are not well delineated or researched. Key gaps and controversies include: (1) Is genetic testing appropriate in symptomatic and asymptomatic individuals without medical actionability? (2) How, if at all, should testing vary based on ethnicity? (3) What are the long-term outcomes of consumer- and research-based genetic testing in presymptomatic PD? (4) What resources are needed for clinical genetic testing, and how is this impacted by models of care and cost-benefit considerations? Addressing these issues will help facilitate the development of consensus and guidelines regarding the approach and access to genetic testing and counseling. This is also needed to guide a multidisciplinary approach that accounts for cultural, geographic, and socioeconomic factors in developing testing guidelines. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Embracing Monogenic Parkinson's Disease: The MJFF Global Genetic PD Cohort.

BACKGROUND: As gene-targeted therapies are increasingly being developed for Parkinson's disease (PD), identifying and characterizing carriers of specific genetic pathogenic variants is imperative. Only a small fraction of the estimated number of subjects with monogenic PD worldwide are currently represented in the literature and availability of clinical data and clinical trial-ready cohorts is limited. OBJECTIVE: The objectives are to (1) establish an international cohort of affected and unaffected individuals with PD-linked variants; (2) provide harmonized and quality-controlled clinical characterization data for each included individual; and (3) further promote collaboration of researchers in the field of monogenic PD. METHODS: We conducted a worldwide, systematic online survey to collect individual-level data on individuals with PD-linked variants in SNCA, LRRK2, VPS35, PRKN, PINK1, DJ-1, as well as selected pathogenic and risk variants in GBA and corresponding demographic, clinical, and genetic data. All registered cases underwent thorough quality checks, and pathogenicity scoring of the variants and genotype-phenotype relationships were analyzed. RESULTS: We collected 3888 variant carriers for our analyses, reported by 92 centers (42 countries) worldwide. Of the included individuals, 3185 had a diagnosis of PD (ie, 1306 LRRK2, 115 SNCA, 23 VPS35, 429 PRKN, 75 PINK1, 13 DJ-1, and 1224 GBA) and 703 were unaffected (ie, 328 LRRK2, 32 SNCA, 3 VPS35, 1 PRKN, 1 PINK1, and 338 GBA). In total, we identified 269 different pathogenic variants; 1322 individuals in our cohort (34%) were indicated as not previously published. CONCLUSIONS: Within the MJFF Global Genetic PD Study Group, we (1) established the largest international cohort of affected and unaffected individuals carrying PD-linked variants; (2) provide harmonized and quality-controlled clinical and genetic data for each included individual; (3) promote collaboration in the field of genetic PD with a view toward clinical and genetic stratification of patients for gene-targeted clinical trials. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A data-driven approach to optimizing clinical study eligibility criteria.

OBJECTIVE: Feasible, safe, and inclusive eligibility criteria are crucial to successful clinical research recruitment. Existing expert-centered methods for eligibility criteria selection may not be representative of real-world populations. This paper presents a novel model called OPTEC (OPTimal Eligibility Criteria) based on the Multiple Attribute Decision Making method boosted by an efficient greedy algorithm. METHODS: It systematically identifies the optimal criteria combination for a given medical condition with the optimal tradeoff among feasibility, patient safety, and cohort diversity. The model offers flexibility in attribute configurations and generalizability to various clinical domains. The model was evaluated on two clinical domains (i.e., Alzheimer's disease and Neoplasm of pancreas) using two datasets (i.e., MIMIC-III dataset and NewYork-Presbyterian/Columbia University Irving Medical Center (NYP/CUIMC) database). RESULTS: We simulated the process of automatically optimizing eligibility criteria according to user-specified prioritization preferences and generated recommendations based on the top-ranked criteria combination accordingly (top 0.41-2.75%) with OPTEC. Harnessing the power of the model, we designed an interactive criteria recommendation system and conducted a case study with an experienced clinical researcher using the think-aloud protocol. CONCLUSIONS: The results demonstrated that OPTEC could be used to recommend feasible eligibility criteria combinations, and to provide actionable recommendations for clinical study designers to construct a feasible, safe, and diverse cohort definition during early study design.

Estimating disease onset from change points of markers measured with error.

Huntington disease is an autosomal dominant, neurodegenerative disease without clearly identified biomarkers for when motor-onset occurs. Current standards to determine motor-onset rely on a clinician's subjective judgment that a patient's extrapyramidal signs are unequivocally associated with Huntington disease. This subjectivity can lead to error which could be overcome using an objective, data-driven metric that determines motor-onset. Recent studies of motor-sign decline-the longitudinal degeneration of motor-ability in patients-have revealed that motor-onset is closely related to an inflection point in its longitudinal trajectory. We propose a nonlinear location-shift marker model that captures this motor-sign decline and assesses how its inflection point is linked to other markers of Huntington disease progression. We propose two estimating procedures to estimate this model and its inflection point: one is a parametric method using nonlinear mixed effects model and the other one is a multi-stage nonparametric approach, which we developed. In an empirical study, the parametric approach was sensitive to correct specification of the mean structure of the longitudinal data. In contrast, our multi-stage nonparametric procedure consistently produced unbiased estimates regardless of the true mean structure. Applying our multi-stage nonparametric estimator to Neurobiological Predictors of Huntington Disease, a large observational study of Huntington disease, leads to earlier prediction of motor-onset compared to the clinician's subjective judgment.

Genomewide Association Studies of LRRK2 Modifiers of Parkinson's Disease.

OBJECTIVE: The aim of this study was to search for genes/variants that modify the effect of LRRK2 mutations in terms of penetrance and age-at-onset of Parkinson's disease. METHODS: We performed the first genomewide association study of penetrance and age-at-onset of Parkinson's disease in LRRK2 mutation carriers (776 cases and 1,103 non-cases at their last evaluation). Cox proportional hazard models and linear mixed models were used to identify modifiers of penetrance and age-at-onset of LRRK2 mutations, respectively. We also investigated whether a polygenic risk score derived from a published genomewide association study of Parkinson's disease was able to explain variability in penetrance and age-at-onset in LRRK2 mutation carriers. RESULTS: A variant located in the intronic region of CORO1C on chromosome 12 (rs77395454; p value = 2.5E-08, beta = 1.27, SE = 0.23, risk allele: C) met genomewide significance for the penetrance model. Co-immunoprecipitation analyses of LRRK2 and CORO1C supported an interaction between these 2 proteins. A region on chromosome 3, within a previously reported linkage peak for Parkinson's disease susceptibility, showed suggestive associations in both models (penetrance top variant: p value = 1.1E-07; age-at-onset top variant: p value = 9.3E-07). A polygenic risk score derived from publicly available Parkinson's disease summary statistics was a significant predictor of penetrance, but not of age-at-onset. INTERPRETATION: This study suggests that variants within or near CORO1C may modify the penetrance of LRRK2 mutations. In addition, common Parkinson's disease associated variants collectively increase the penetrance of LRRK2 mutations. ANN NEUROL 2021;90:82-94.

Plasma Glucosylsphingosine in GBA1 Mutation Carriers with and without Parkinson's Disease.

BACKGROUND: Biallelic mutations in the GBA1 gene encoding glucocerebrosidase cause Gaucher's disease, whereas heterozygous carriers are at risk for Parkinson's disease (PD). Glucosylsphingosine is a clinically meaningful biomarker of Gaucher's disease but could not be assayed previously in heterozygous GBA1 carriers. OBJECTIVE: The aim of this study was to assess plasma glucosylsphingosine levels in GBA1 N370S carriers with and without PD. METHODS: Glucosylsphingosine, glucosylceramide, and four other lipids were quantified in plasma from N370S heterozygotes with (n = 20) or without (n = 20) PD, healthy controls (n = 20), idiopathic PD (n = 20), and four N370S homozygotes (positive controls; Gaucher's/PD) using quantitative ultra-performance liquid chromatography tandem mass spectrometry. RESULTS: Plasma glucosylsphingosine was significantly higher in N370S heterozygotes compared with noncarriers, independent of disease status. As expected, Gaucher's/PD cases showed increases in both glucocerebrosidase substrates, glucosylsphingosine and glucosylceramide. CONCLUSIONS: Plasma glucosylsphingosine accumulation in N370S heterozygotes shown in this study opens up its future assessment as a clinically meaningful biomarker of GBA1-PD. © 2021 International Parkinson and Movement Disorder Society.

Constructing disease onset signatures using multi-dimensional network-structured biomarkers.

Potential disease-modifying therapies for neurodegenerative disorders need to be introduced prior to the symptomatic stage in order to be effective. However, current diagnosis of neurological disorders mostly rely on measurements of clinical symptoms and thus only identify symptomatic subjects in their late disease course. Thus, it is of interest to select and integrate biomarkers that may reflect early disease-related pathological changes for earlier diagnosis and recruiting pre-sypmtomatic subjects in a prevention clinical trial. Two sources of biological information are relevant to the construction of biomarker signatures for time to disease onset that is subject to right censoring. First, biomarkers' effects on disease onset may vary with a subject's baseline disease stage indicated by a particular marker. Second, biomarkers may be connected through networks, and their effects on disease may be informed by this network structure. To leverage these information, we propose a varying-coefficient hazards model to induce double smoothness over the dimension of the disease stage and over the space of network-structured biomarkers. The distinctive feature of the model is a non-parametric effect that captures non-linear change according to the disease stage and similarity among the effects of linked biomarkers. For estimation and feature selection, we use kernel smoothing of a regularized local partial likelihood and derive an efficient algorithm. Numeric simulations demonstrate significant improvements over existing methods in performance and computational efficiency. Finally, the methods are applied to our motivating study, a recently completed study of Huntington's disease (HD), where structural brain imaging measures are used to inform age-at-onset of HD and assist clinical trial design. The analysis offers new insights on the structural network signatures for premanifest HD subjects.

Age of Onset of Huntington's Disease in Carriers of Reduced Penetrance Alleles.

BACKGROUND: Age of manifest Huntington's disease (HD) onset correlates with number of CAG repeats in the huntingtin gene. Little is known about onset with 36 to 39 repeats, the "reduced penetrance" (RP) range. OBJECTIVES: We provide allele-specific estimates of HD penetrance (diagnostic confidence level of 4) for RP allele carriers. METHODS: We analyzed 431 pre-manifest RP allele carriers from Enroll-HD, the largest prospective observational HD study. Cumulative penetrance (CP) was estimated from Kaplan-Meier curves. RESULTS: No one with 36 repeats (n = 25) phenoconverted. CP for 38 repeats (n = 120) was 32% (95% confidence interval [CI] 0%-55%) and 51% (CI, 10%-73%) by ages 70 and 75, respectively, and 68% (CI, 46%-81%) and 81% (CI, 58%-92%) by ages 70 and 75 for 39 repeats (n = 253). CP was not estimable at those ages for 37 repeats (n = 33). CONCLUSIONS: Differences by RP-range repeat length did not reach significance with a 3-year median follow-up duration among censored individuals. © 2021 International Parkinson and Movement Disorder Society.

Time-varying proportional odds model for mega-analysis of clustered event times.

Mega-analysis, or the meta-analysis of individual data, enables pooling and comparing multiple studies to enhance estimation and power. A challenge in mega-analysis is estimating the distribution for clustered, potentially censored event times where the dependency structure can introduce bias if ignored. We propose a new proportional odds model with unknown, time-varying coefficients, and random effects. The model directly captures event dependencies, handles censoring using pseudo-values, and permits a simple estimation by transforming the model into an easily estimable additive logistic mixed effect model. Our method consistently estimates the distribution for clustered event times even under covariate-dependent censoring. Applied to three observational studies of Huntington's disease, our method provides, for the first time in the literature, evidence of similar conclusions about motor and cognitive impairments in all studies despite different recruitment criteria.

Genetic testing for Parkinson disease: current practice, knowledge, and attitudes among US and Canadian movement disorders specialists.

PURPOSE: Genetic testing for Parkinson disease (PD) has not been widely used in clinical practice. In preparation for upcoming precision medicine-designed clinical trials for GBA and LRRK2, we evaluated movement disorders specialists' current practice, knowledge, attitudes, and barriers to genetic testing in PD. METHODS: An anonymous questionnaire was sent to movement disorders specialists at 146 Parkinson Study Group (PSG) sites in the United States (n = 131) and Canada (n = 15) to assess their knowledge and attitudes about genetic testing for PD. RESULTS: One hundred seventy-eight (47.6%) PSG clinicians completed the questionnaire. Forty-one percent of respondents had not referred any PD patients for genetic testing in the last year and >80% reported referring fewer than 11 patients over the same period. Most common reasons for not referring for genetic testing included lack of insurance coverage/cost to the patient and lack of perceived utility. On a scale of 0-100, the mean level of comfort in respondents' own ability to genetically counsel PD patients on GBA and LRRK2 was 52 (SD = 28). Sixty percent of clinicians correctly answered all questions about the inheritance and penetrance of GBA and LRRK2 variants. CONCLUSIONS: There is an urgent need to increase knowledge and reduce practical barriers to genetic counseling and testing in PD.

Correction: Genetic testing for Parkinson disease: current practice, knowledge, and attitudes among US and Canadian movement disorders specialists.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Predictive testing for neurodegenerative diseases in the age of next-generation sequencing.

The availability and cost of next-generation sequencing (NSG) now allow testing large numbers of genes simultaneously. However, the gold standard for predictive testing has been to test only for a known family mutation or confirmed family disease. The goal of this study was to investigate the psychological impact of predictive testing for autosomal dominant neurodegenerative diseases without a known family mutation using next-generation sequencing panels compared to single-gene testing of a known family mutation. Fourteen individuals from families with a known mutation and 10 individuals with unknown family mutations participated. Participants completed questionnaires on demographics, genetic knowledge, and psychological measures of anxiety, depression, perceived personal control, rumination, and intolerance to uncertainty at baseline and 1 and 6 months after receiving results. Decision regret was measured 1 and 6 months after receiving results. Participants completed a modified Huntington disease genetic testing protocol with genetic counseling and neurological and psychological evaluation. Genetic testing of either the known family mutation or an NGS panel of neurodegenerative disease genes was performed. Semi-structured interviews were performed at 6 months post-results about their experience. Two-sample t tests were performed on data collected at each time point to identify significant between-group differences in demographic variables, baseline psychological scores, and baseline genetic knowledge scores. Within-group change over time was assessed by a mixed-effects model. Results of this study indicate that NGS panels for predictive testing for neurodegenerative disease are safe and beneficial to participants when performed within a modified HD protocol. Though significant differences in psychological outcomes were found, these differences may have been driven by genetic results and baseline psychological differences between individuals within the groups. Participants did not regret their decision to test and were largely pleased with the testing protocol.

Time-varying Hazards Model for Incorporating Irregularly Measured, High-Dimensional Biomarkers.

Clinical studies with time-to-event outcomes often collect measurements of a large number of time-varying covariates over time (e.g., clinical assessments or neuroimaging biomarkers) to build time-sensitive prognostic model. An emerging challenge is that due to resource-intensive or invasive (e.g., lumbar puncture) data collection process, biomarkers may be measured infrequently and thus not available at every observed event time point. Lever-aging all available, infrequently measured time-varying biomarkers to improve prognostic model of event occurrence is an important and challenging problem. In this paper, we propose a kernel-smoothing based approach to borrow information across subjects to remedy infrequent and unbalanced biomarker measurements under a time-varying hazards model. A penalized pseudo-likelihood function is proposed for estimation, and an efficient augmented penalization minimization algorithm related to the alternating direction method of multipliers (ADMM) is adopted for computation. Under some regularity conditions to carefully control approximation bias and stochastic variability, we show that even in the presence of ultra-high dimensionality, the proposed method selects important biomarkers with high probability. Through extensive simulation studies, we demonstrate superior performance in terms of estimation and selection performance compared to alternative methods. Finally, we apply the proposed method to analyze a recently completed real world study to model time to disease conversion using longitudinal, whole brain structural magnetic resonance imaging (MRI) biomarkers, and show a substantial improvement in performance over current standards including using baseline measures only.

Heritability and genetic variance of dementia with Lewy bodies.

Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinson's disease (PD) or Alzheimer's disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants.