Dataset Information

Refining the diagnosis of Huntington disease: the PREDICT-HD study.

ABSTRACT: Participants with the gene expansion for Huntington disease (HD) but not yet diagnosed were evaluated annually. Unidimensional diagnosis (UD) was a motor diagnosis defined as a diagnostic confidence level (DCL) of 4 (unequivocal motor signs, ?99% confidence) on the standardized motor exam of the Unified Huntington Disease Rating Scale (UHDRS). Multidimensional diagnosis (MD) was defined as answering yes on Question 80 (Q80) of the UHDRS, ?99% confidence of manifest HD based on the entire UHDRS. Motor, cognitive, and behavioral measures of phenotype at first diagnosis were compared by t-tests between participants diagnosed via motor exam (UD) and those diagnosed via multidimensional input (MD). Cluster analysis identified clusters based on UHDRS domains.186 participants received a diagnosis of HD during a maximum of 6.4 years of follow-up. In 108 (58.1%) the diagnosis by MD and UD occurred simultaneously, while in 69 (37.1%) the diagnosis by MD occurred prior to UD. Participants who were diagnosed by MD prior to UD were less impaired on motor (12.2 ± 6.7 vs. 22.4 ± 9.3, p < 0.0001), and cognitive (290.7 ± 56.2 vs. 258.0 ± 53.7, p = 0.0002), but not behavioral measures (16.3 ± 21.2 vs. 18.6 ± 22.1, p = 0.49) when compared with those diagnosed simultaneously. Cluster analysis identified three clusters that represented primarily cognitively impaired, behaviorally impaired, and cognitively preserved phenotypes. A multidimensional method results in an earlier diagnosis with less motor and cognitive impairment than a motor diagnosis. Findings have implications for designing preventive trials and providing clinical care in prodromal HD.

SUBMITTER: Biglan KM

PROVIDER: S-EPMC3613616 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Refining the diagnosis of Huntington disease: the PREDICT-HD study.

Biglan Kevin M KM Zhang Ying Y Long Jeffrey D JD Geschwind Michael M Kang Gail A GA Killoran Annie A Lu Wenjing W McCusker Elizabeth E Mills James A JA Raymond Lynn A LA Testa Claudia C Wojcieszek Joanne J Paulsen Jane S JS

Frontiers in aging neuroscience 20130402

Participants with the gene expansion for Huntington disease (HD) but not yet diagnosed were evaluated annually. Unidimensional diagnosis (UD) was a motor diagnosis defined as a diagnostic confidence level (DCL) of 4 (unequivocal motor signs, ≥99% confidence) on the standardized motor exam of the Unified Huntington Disease Rating Scale (UHDRS). Multidimensional diagnosis (MD) was defined as answering yes on Question 80 (Q80) of the UHDRS, ≥99% confidence of manifest HD based on the entire UHDRS. ...[more]

PMID: 23565093

Similar Datasets

Project description:The purpose of this project is to make clinical measurements from the PREDICT-HD consortium available through the dbGaP mechanism. The phenotype data will first be converted into a community open standard and subsequently exported to dbGaP for archival and open access distribution of the results of the studies. This will permit members of the scientific community to utilize a permanent resource for investigating the interactions of phenotypes upon an international cohort of early Huntington Disease. In version 2 cut of the data we provided HD CAG repeat lengths for both alleles as well as enrollment age of all participants. We have also generated unique identifiers prospectively compatible with the larger initiative GWAS in Huntington's Disease project (also on DbGaP). As such, the version 1 cut of the data was mainly proof of concept and should be deprecated. Going forward, all updates will add-on to version 2 cut of the data. In version 3 cut of the data, we provided baseline or the first usable MRI T1-weighted imaging analysis subcortical and cortical segmentations and cortical parcellations based on a customized Freesurfer 5.2 pipeline developed at The University of Iowa. The customizations to the standard pipeline were mainly to improve bias field correction and image normalization such that segmentation of gray, white, internal csf, dura and surface CSF are optimized for the Freesurfer pipeline. There are 1111 subjects with results in this data release. In version 4 cut of the data, we provided all longitudinal clinical measurements for all subjects (total of 1476) assessmented or enrolled through the end of 2013. Additionally, we are providing measurements on 39 baseline FDG PET images spatially normalized by SPM5 into MNI space, relative regional metabolic values computed in 120 volumes of interest (VOI) defined in the Automated Anatomical Labeling (AAL) Atlas (<a href="http://www.ncbi.nlm.nih.gov/pubmed/11771995">Tzourio-Mazoyer et al. 2002</a>), and global metabolic values calculated by SPM standard mean voxel value (within per image fullmean/8 mask). This project is a funded ancillary study of <a href="https://www.predict-hd.net/">PREDICT-HD</a>. In this version 5 cut of the data, we are providing the first of many forthcoming results from ancilliary studies of PREDICT-HD. In this data cut, we provide individual subject results derived from structural MRI data. The earliest MRI session for each subject was used. The results summarized represent source based morphometry loading coefficients for 23 components (see: "Patterns of Co-Occurring Gray Matter Concentration Loss across the Huntington Disease Prodrome", Ciarochi et al., 2016, <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=27708610">Front Neurol. 2016</a>; 7: 147, Published online 2016 Sep 21. doi: 10.3389/fneur.2016.00147]. For sample information please link to: <a href="http://ccr.coriell.org/Sections/Collections/NINDS/PredictHD.aspx?PgId=746&coll=ND">PREDICT-HD Biospecimen Resources</a>

Project description:Background and objectivesThe variable CAG repeat expansion in the huntingtin gene and its inverse relationship to motor dysfunction onset are fundamental features of Huntington disease (HD). However, the wider phenotype (including non-motor features) at particular CAG lengths, ages, and functional levels is less well-characterized. The large number of participants in the Enroll-HD observational study enables the development of a phenotype atlas that summarizes the range and distribution of HD phenotypes, including outliers and possible clusters, with respect to various CAG repeat lengths, age ranges, and declining functional levels.MethodsEnroll-HD is an ongoing prospective longitudinal observational study that collects natural history data, releasing periodic data sets, in people with HD (PwHD) and controls. Core assessments at annual visits focus on behavioral, cognitive, motor, and functional status. Periodic data set 5, used for the development of the first iteration of the Enroll-HD Phenotype Atlas (EHDPA), included all eligible data collected through October 31, 2020. The atlas is based on subsets (cells) of descriptive data for all motor, cognitive, psychiatric, and functional measures that are routinely collected at most Enroll-HD sites, analyzed by single CAG lengths and 5-year age blocks.ResultsData from 42,840 visits from 15,982 unique PwHD were available for analysis. At baseline, participants had a mean ± SD age of 48.9 ± 13.9 years and CAG repeat length of 43.4 ± 3.6 and 54.1% were female. The EHDPA includes 223 age-by-CAG subsets for CAG repeats between 36 and 69 with five-year age brackets starting from 20-24 years up to 85-89 years. The atlas can be browsed at enroll-hd.org/for-researchers/atlas-of-hd-phenotype/.DiscussionThe EHDPA summarizes the spectrum and distribution of HD phenotypes, including outliers and possible clusters, in all domains of disease involvement for the range of CAG repeat lengths, ages, and functional levels. Its availability in an easy-to-use online format will assist clinicians in tracking disease progression in PwHD by identifying phenotypic features most associated with loss of function and enabling conversations related to prognosis. The observable patterns in the EHDPA should also catalyze more formal multidomain characterization of motor, cognitive, and psychiatric progression and their relationships to functional decline and disease modifiers.Trial registration informationEnroll-HD is registered with clinicaltrials.gov: NCT01574053.

Dataset Information

Refining the diagnosis of Huntington disease: the PREDICT-HD study.

Publications

Refining the diagnosis of Huntington disease: the PREDICT-HD study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets