Genetic Adverse Selection: Evidence from Long-Term Care Insurance and Huntington Disease

Individual, personalized genetic information is increasingly available, leading to the possibility of greater adverse selection over time, particularly in individual-payer insurance markets; this selection could impact the viability of these markets. We use data on individuals at risk for Huntington disease (HD), a degenerative neurological disorder with significant effects on morbidity, to estimate adverse selection in long-term care insurance. We find strong evidence of adverse selection: individuals who carry the HD genetic mutation are up to 5 times as likely as the general population to own long-term care insurance. We use these estimates to make predictions about the future of this market as genetic information increases. We argue that even relatively limited increases in genetic information may threaten the viability of private long-term care insurance.

CAG repeat not polyglutamine length determines timing of Huntington’s disease onset

Variable, glutamine-encoding, CAA interruptions indicate that a property of the uninterrupted HTT CAG repeat sequence, distinct from the length of huntingtin’s polyglutamine segment, dictates the rate at which Huntington’s disease (HD) develops. The timing of onset shows no significant association with HTT cis-eQTLs but is influenced, sometimes in a sex-specific manner, by polymorphic variation at multiple DNA maintenance genes, suggesting that the special onset-determining property of the uninterrupted CAG repeat is a propensity for length instability that leads to its somatic expansion. Additional naturally occurring genetic modifier loci, defined by GWAS, may influence HD pathogenesis through other mechanisms. These findings have profound implications for the pathogenesis of HD and other repeat diseases and question the fundamental premise that polyglutamine length determines the rate of pathogenesis in the “polyglutamine disorders.

A randomized, double-blind, placebo-controlled trial of coenzyme Q10 in Huntington disease

Objective: To test the hypothesis that chronic treatment of early-stage Huntington disease (HD) with high-dose coenzyme Q10 (CoQ) will slow the progressive functional decline of HD. Methods: We performed a multicenter randomized, double-blind, placebo-controlled trial. Patients with early-stage HD (n = 609) were enrolled at 48 sites in the United States, Canada, and Australia from 2008 to 2012. Patients were randomized to receive either CoQ 2,400 mg/d or matching placebo, then followed for 60 months. The primary outcome variable was the change from baseline to month 60 in Total Functional Capacity score (for patients who survived) combined with time to death (for patients who died) analyzed using a joint-rank analysis approach. Results: An interim analysis for futility revealed a conditional power of <5% for the primary analysis, prompting premature conclusion in July 2014. No statistically significant differences were seen between treatment groups for the primary or secondary outcome measures. CoQ was generally safe and well-tolerated throughout the study. Conclusions: These data do not justify use of CoQ as a treatment to slow functional decline in HD

Genetic risk underlying psychiatric and cognitive symptoms in Huntington’s Disease

Background Huntington’s disease (HD) is an inherited neurodegenerative disorder caused by an expanded CAG repeat in the HTT gene. It is diagnosed following a standardized exam of motor control and often presents with cognitive decline and psychiatric symptoms. Recent studies have detected genetic loci modifying the age at onset of motor symptoms in HD, but genetic factors influencing cognitive and psychiatric presentations are unknown. Methods We tested the hypothesis that psychiatric and cognitive symptoms in HD are influenced by the same common genetic variation as in the general population by constructing polygenic risk scores from large genome-wide association studies of psychiatric and neurodegenerative disorders, and of intelligence, and testing for correlation with the presence of psychiatric and cognitive symptoms in a large sample (n=5160) of HD patients. Results Polygenic risk score for major depression was associated specifically with increased risk of depression in HD, as was schizophrenia risk score with psychosis and irritability. Cognitive impairment and apathy were associated with reduced polygenic risk score for intelligence. Conclusions Polygenic risk scores for psychiatric disorders, particularly depression and schizophrenia, are associated with increased risk of the corresponding psychiatric symptoms in HD, suggesting a common genetic liability. However, the genetic liability to cognitive impairment and apathy appears to be distinct from other psychiatric symptoms in HD. No associations were observed between HD symptoms and risk scores for other neurodegenerative disorders. These data provide a rationale for treatments effective in depression and schizophrenia to be used to treat depression and psychotic symptoms in HD

Discovery and functional prioritization of Parkinson's disease candidate genes from large-scale whole exome sequencing.

BACKGROUND: Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson's disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models. RESULTS: Assuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes-GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C-also showed evidence consistent with genetic replication. CONCLUSIONS: By integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies

What Do Patients Say About Their Disease Symptoms? Deep Multilabel Text Classification With Human-in-the-Loop Curation for Automatic Labeling of Patient Self Reports of Problems

The USA Food and Drug Administration has accorded increasing importance to patient-reported problems in clinical and research settings. In this paper, we explore one of the largest online datasets comprising 170,141 open-ended self-reported responses (called "verbatims") from patients with Parkinson's (PwPs) to questions about what bothers them about their Parkinson's Disease and how it affects their daily functioning, also known as the Parkinson's Disease Patient Report of Problems. Classifying such verbatims into multiple clinically relevant symptom categories is an important problem and requires multiple steps - expert curation, a multi-label text classification (MLTC) approach and large amounts of labelled training data. Further, human annotation of such large datasets is tedious and expensive. We present a novel solution to this problem where we build a baseline dataset using 2,341 (of the 170,141) verbatims annotated by nine curators including clinical experts and PwPs. We develop a rules based linguistic-dictionary using NLP techniques and graph database-based expert phrase-query system to scale the annotation to the remaining cohort generating the machine annotated dataset, and finally build a Keras-Tensorflow based MLTC model for both datasets. The machine annotated model significantly outperforms the baseline model with a F1-score of 95% across 65 symptom categories on a held-out test set

Genetic adverse selection: Evidence from long-term care insurance and Huntington disease

Individual, personalized genetic information is increasingly available, leading to the possibility of greater adverse selection over time, particularly in individual-payer insurance markets. We use data on individuals at risk for Huntington disease (HD), a degenerative neurological disorder with significant effects on morbidity, to estimate adverse selection in long-term care insurance. We find strong evidence of adverse selection: individuals who carry the HD genetic mutation are up to 5 times as likely as the general population to own long-term care insurance. This finding is supported both by comparing individuals at risk for HD to those in the general population and by comparing across tested individuals in the HD-risk population with and without the HD mutation.Adverse selection Long-term care insurance Huntington disease Genetic testing

Relationship of Mediterranean Diet and Caloric Intake to Phenoconversion in Huntington Disease

ImportanceAdherence to Mediterranean-type diet (MeDi) may delay onset of Alzheimer and Parkinson diseases. Whether adherence to MeDi affects time to phenoconversion in Huntington disease (HD), a highly penetrant, single-gene disorder, is unknown.ObjectivesTo determine if MeDi modifies the time to clinical onset of HD (phenoconversion) in premanifest carriers participating in Prospective Huntington at Risk Observational Study (PHAROS), and to examine the effects of body mass index and caloric intake on time to phenoconversion.Design, setting, and participantsA prospective cohort study of 41 Huntington study group sites in the United States and Canada involving 1001 participants enrolled in PHAROS between July 1999 and January 2004 who were followed up every 9 months until 2010. A total of 211 participants aged 26 to 57 years had an expanded CAG repeat length (≥ 37).ExposureA semiquantitative food frequency questionnaire was administered 33 months after baseline. We calculated daily gram intake for dairy, meat, fruit, vegetables, legumes, cereals, fish, monounsaturated and saturated fatty acids, and alcohol and constructed MeDi scores (0-9); higher scores indicate higher adherence. Demographics, medical history, body mass index, and Unified Huntington's Disease Rating Scale (UHDRS) score were collected.Main outcome and measureCox proportional hazards regression models to determine the association of MeDi and phenoconversion. RESULTS Age, sex, caloric intake, education status, and UHDRS motor scores did not differ among MeDi tertiles (0-3, 4-5, and 6-9). The highest body mass index was associated with the lowest adherence to MeDi. Thirty-one participants phenoconverted. In a model adjusted for age, CAG repeat length, and caloric intake, MeDi was not associated with phenoconversion (P for trend = 0.14 for tertile of MeDi, and P = .22 for continuous MeDi). When individual components of MeDi were analyzed, higher dairy consumption (hazard ratio, 2.36; 95% CI, 1.0-5.57; P = .05) and higher caloric intake (P = .04) were associated with risk of phenoconversion.Conclusions and relevanceMeDi was not associated with phenoconversion; however, higher consumption of dairy products had a 2-fold increased risk and may be a surrogate for lower urate levels (associated with faster progression in manifest HD). Studies of diet and energy expenditure in premanifest HD may provide data for interventions to modify specific components of diet that may delay the onset of HD