Application of Machine Learning Models to Evaluate Hypoglycemia Risk in Type 2 Diabetes.

INTRODUCTION: To identify predictors of hypoglycemia and five other clinical and economic outcomes among treated patients with type 2 diabetes (T2D) using machine learning and structured data from a large, geographically diverse administrative claims database. METHODS: A retrospective cohort study design was applied to Optum Clinformatics claims data indexed on first antidiabetic prescription date. A hypothesis-free, Bayesian machine learning analytics platform (GNS Healthcare REFS™: Reverse Engineering and Forward Simulation) was used to build ensembles of generalized linear models to predict six outcomes defined in patients' 1-year post-index claims history, including hypoglycemia, antidiabetic class persistence, glycated hemoglobin (HbA1c) target attainment, HbA1c change, T2D-related inpatient admissions, and T2D-related medical costs. A unified set of 388 variables defined in patients' 1-year pre-index claims history constituted the set of predictors for all REFS models. RESULTS: The derivation cohort comprised 453,487 patients with a T2D diagnosis between 2014 and 2017. Patients with comorbid conditions had the highest risk of hypoglycemia, including those with prior hypoglycemia (odds ratio [OR] = 25.61) and anemia (OR = 1.29). Other identified risk factors included insulin (OR = 2.84) and sulfonylurea use (OR = 1.80). Biguanide use (OR = 0.75), high blood glucose (> 125 mg/dL vs. < 100 mg/dL, OR = 0.47; 100-125 mg/dL vs. < 100 mg/dL, OR = 0.53), and missing blood glucose test (OR = 0.40) were associated with reduced risk of hypoglycemia. Area under the curve (AUC) of the hypoglycemia model in held-out testing data was 0.77. Patients in the top 15% of predicted hypoglycemia risk constituted 50% of observed hypoglycemic events, 26% of T2D-related inpatient admissions, and 24% of all T2D-related medical costs. CONCLUSIONS: Machine learning models built within high-dimensional, real-world data can predict patients at risk of clinical outcomes with a high degree of accuracy, while uncovering important factors associated with outcomes that can guide clinical practice. Targeted interventions towards these patients may help reduce hypoglycemia risk and thereby favorably impact associated economic outcomes relevant to key stakeholders.

Large-scale identification of clinical and genetic predictors of motor progression in patients with newly diagnosed Parkinson's disease: a longitudinal cohort study and validation.

BACKGROUND: Better understanding and prediction of progression of Parkinson's disease could improve disease management and clinical trial design. We aimed to use longitudinal clinical, molecular, and genetic data to develop predictive models, compare potential biomarkers, and identify novel predictors for motor progression in Parkinson's disease. We also sought to assess the use of these models in the design of treatment trials in Parkinson's disease. METHODS: A Bayesian multivariate predictive inference platform was applied to data from the Parkinson's Progression Markers Initiative (PPMI) study (NCT01141023). We used genetic data and baseline molecular and clinical variables from patients with Parkinson's disease and healthy controls to construct an ensemble of models to predict the annual rate of change in combined scores from the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) parts II and III. We tested our overall explanatory power, as assessed by the coefficient of determination (R2), and replicated novel findings in an independent clinical cohort from the Longitudinal and Biomarker Study in Parkinson's disease (LABS-PD; NCT00605163). The potential utility of these models for clinical trial design was quantified by comparing simulated randomised placebo-controlled trials within the out-of-sample LABS-PD cohort. FINDINGS: 117 healthy controls and 312 patients with Parkinson's disease from the PPMI study were available for analysis, and 317 patients with Parkinson's disease from LABS-PD were available for validation. Our model ensemble showed strong performance within the PPMI cohort (five-fold cross-validated R2 41%, 95% CI 35-47) and significant-albeit reduced-performance in the LABS-PD cohort (R2 9%, 95% CI 4-16). Individual predictive features identified from PPMI data were confirmed in the LABS-PD cohort. These included significant replication of higher baseline MDS-UPDRS motor score, male sex, and increased age, as well as a novel Parkinson's disease-specific epistatic interaction, all indicative of faster motor progression. Genetic variation was the most useful predictive marker of motor progression (2·9%, 95% CI 1·5-4·3). CSF biomarkers at baseline showed a more modest (0·3%, 95% CI 0·1-0·5) but still significant effect on prediction of motor progression. The simulations (n=5000) showed that incorporating the predicted rates of motor progression (as assessed by the annual change in MDS-UPDRS score) into the final models of treatment effect reduced the variability in the study outcome, allowing significant differences to be detected at sample sizes up to 20% smaller than in naive trials. INTERPRETATION: Our model ensemble confirmed established and identified novel predictors of Parkinson's disease motor progression. Improvement of existing prognostic models through machine-learning approaches should benefit trial design and evaluation, as well as clinical disease monitoring and treatment. FUNDING: Michael J Fox Foundation for Parkinson's Research and National Institute of Neurological Disorders and Stroke.

The 4p16.3 Parkinson Disease Risk Locus Is Associated with GAK Expression and Genes Involved with the Synaptic Vesicle Membrane.

Genome-wide association studies (GWAS) have identified the GAK/DGKQ/IDUA region on 4p16.3 among the top three risk loci for Parkinson's disease (PD), but the specific gene and risk mechanism are unclear. Here, we report transcripts containing the 3' clathrin-binding domain of GAK identified by RNA deep-sequencing in post-mortem human brain tissue as having increased expression in PD. Furthermore, carriers of 4p16.3 PD GWAS risk SNPs show decreased expression of one of these transcripts, GAK25 (Gencode Transcript 009), which correlates with the expression of genes functioning in the synaptic vesicle membrane. Together, these findings provide strong evidence for GAK clathrin-binding- and J-domain transcripts' influence on PD pathogenicity, and for a role for GAK in regulating synaptic function in PD.

Correction: RNA Sequence Analysis of Human Huntington Disease Brain Reveals an Extensive Increase in Inflammatory and Developmental Gene Expression.

[This corrects the article DOI: 10.1371/journal.pone.0143563.].

The HTT CAG-Expansion Mutation Determines Age at Death but Not Disease Duration in Huntington Disease.

Huntington disease (HD) is caused by an expanded HTT CAG repeat that leads in a length-dependent, completely dominant manner to onset of a characteristic movement disorder. HD also displays early mortality, so we tested whether the expanded CAG repeat exerts a dominant influence on age at death and on the duration of clinical disease. We found that, as with clinical onset, HD age at death is determined by expanded CAG-repeat length and has no contribution from the normal CAG allele. Surprisingly, disease duration is independent of the mutation's length. It is also unaffected by a strong genetic modifier of HD motor onset. These findings suggest two parsimonious alternatives. (1) HD pathogenesis is driven by mutant huntingtin, but before or near motor onset, sufficient CAG-driven damage occurs to permit CAG-independent processes and then lead to eventual death. In this scenario, some pathological changes and their clinical correlates could still worsen in a CAG-driven manner after disease onset, but these CAG-related progressive changes do not themselves determine duration. Alternatively, (2) HD pathogenesis is driven by mutant huntingtin acting in a CAG-dependent manner with different time courses in multiple cell types, and the cellular targets that lead to motor onset and death are different and independent. In this scenario, processes driven by HTT CAG length lead directly to death but not via the striatal pathology associated with motor manifestations. Each scenario has important ramifications for the design and testing of potential therapeutics, especially those aimed at preventing or delaying characteristic motor manifestations.

RNA Sequence Analysis of Human Huntington Disease Brain Reveals an Extensive Increase in Inflammatory and Developmental Gene Expression.

Huntington's Disease (HD) is a devastating neurodegenerative disorder that is caused by an expanded CAG trinucleotide repeat in the Huntingtin (HTT) gene. Transcriptional dysregulation in the human HD brain has been documented but is incompletely understood. Here we present a genome-wide analysis of mRNA expression in human prefrontal cortex from 20 HD and 49 neuropathologically normal controls using next generation high-throughput sequencing. Surprisingly, 19% (5,480) of the 28,087 confidently detected genes are differentially expressed (FDR<0.05) and are predominantly up-regulated. A novel hypothesis-free geneset enrichment method that dissects large gene lists into functionally and transcriptionally related groups discovers that the differentially expressed genes are enriched for immune response, neuroinflammation, and developmental genes. Markers for all major brain cell types are observed, suggesting that HD invokes a systemic response in the brain area studied. Unexpectedly, the most strongly differentially expressed genes are a homeotic gene set (represented by Hox and other homeobox genes), that are almost exclusively expressed in HD, a profile not widely implicated in HD pathogenesis. The significance of transcriptional changes of developmental processes in the HD brain is poorly understood and warrants further investigation. The role of inflammation and the significance of non-neuronal involvement in HD pathogenesis suggest anti-inflammatory therapeutics may offer important opportunities in treating HD.

Study of plasma-derived miRNAs mimic differences in Huntington's disease brain.

BACKGROUND: Biomarkers for Huntington's disease progression could accelerate therapeutic developments and improve patient care. Brain microRNAs relating to clinical features of Huntington's disease may represent a potential Huntington's disease biomarker in blood. OBJECTIVE: This study was undertaken to examine candidate microRNAs in plasma to determine whether changes observed in HD brains are detectable in peripheral samples. METHODS: Four microRNAs from 26 manifest Huntington's disease, four asymptomatic Huntington's disease gene carriers, and eight controls were quantified in plasma using reverse transcription quantitative polymerase chain reaction. Linear regression was used to assess microRNA levels across control, asymptomatic gene carriers, and manifest patients. RESULTS: miR-10b-5p (P = 0.0068) and miR-486-5p (P = 0.044) were elevated in Huntington's disease plasma. miR-10b-5p was decreased in asymptomatic gene carriers as compared with patients with Huntington's disease (P = 0.049), but no difference between asymptomatic gene carriers and healthy controls was observed (P = 0.24). CONCLUSIONS: These findings suggest that microRNA changes observed in Huntington's disease brain may be detectable in plasma and have potential clinical utility.

miR-10b-5p expression in Huntington's disease brain relates to age of onset and the extent of striatal involvement.

BACKGROUND: MicroRNAs (miRNAs) are small non-coding RNAs that recognize sites of complementarity of target messenger RNAs, resulting in transcriptional regulation and translational repression of target genes. In Huntington's disease (HD), a neurodegenerative disease caused by a trinucleotide repeat expansion, miRNA dyregulation has been reported, which may impact gene expression and modify the progression and severity of HD. METHODS: We performed next-generation miRNA sequence analysis in prefrontal cortex (Brodmann Area 9) from 26 HD, 2 HD gene positive, and 36 control brains. Neuropathological information was available for all HD brains, including age at disease onset, CAG-repeat size, Vonsattel grade, and Hadzi-Vonsattel striatal and cortical scores, a continuous measure of the extent of neurodegeneration. Linear models were performed to examine the relationship of miRNA expression to these clinical features, and messenger RNA targets of associated miRNAs were tested for gene ontology term enrichment. RESULTS: We identified 75 miRNAs differentially expressed in HD brain (FDR q-value <0.05). Among the HD brains, nine miRNAs were significantly associated with Vonsattel grade of neuropathological involvement and three of these, miR-10b-5p, miR-10b-3p, and miR-302a-3p, significantly related to the Hadzi-Vonsattel striatal score (a continuous measure of striatal involvement) after adjustment for CAG length. Five miRNAs (miR-10b-5p, miR-196a-5p, miR-196b-5p, miR-10b-3p, and miR-106a-5p) were identified as having a significant relationship to CAG length-adjusted age of onset including miR-10b-5p, the mostly strongly over-expressed miRNA in HD cases. Although prefrontal cortex was the source of tissue profiled in these studies, the relationship of miR-10b-5p expression to striatal involvement in the disease was independent of cortical involvement. Correlation of miRNAs to the clinical features clustered by direction of effect and the gene targets of the observed miRNAs showed association to processes relating to nervous system development and transcriptional regulation. CONCLUSIONS: These results demonstrate that miRNA expression in cortical BA9 provides insight into striatal involvement and support a role for these miRNAs, particularly miR-10b-5p, in HD pathogenicity. The miRNAs identified in our studies of postmortem brain tissue may be detectable in peripheral fluids and thus warrant consideration as accessible biomarkers for disease stage, rate of progression, and other important clinical characteristics of HD.

MicroRNAs located in the Hox gene clusters are implicated in huntington's disease pathogenesis.

Transcriptional dysregulation has long been recognized as central to the pathogenesis of Huntington's disease (HD). MicroRNAs (miRNAs) represent a major system of post-transcriptional regulation, by either preventing translational initiation or by targeting transcripts for storage or for degradation. Using next-generation miRNA sequencing in prefrontal cortex (Brodmann Area 9) of twelve HD and nine controls, we identified five miRNAs (miR-10b-5p, miR-196a-5p, miR-196b-5p, miR-615-3p and miR-1247-5p) up-regulated in HD at genome-wide significance (FDR q-value<0.05). Three of these, miR-196a-5p, miR-196b-5p and miR-615-3p, were expressed at near zero levels in control brains. Expression was verified for all five miRNAs using reverse transcription quantitative PCR and all but miR-1247-5p were replicated in an independent sample (8HD/8C). Ectopic miR-10b-5p expression in PC12 HTT-Q73 cells increased survival by MTT assay and cell viability staining suggesting increased expression may be a protective response. All of the miRNAs but miR-1247-5p are located in intergenic regions of Hox clusters. Total mRNA sequencing in the same samples identified fifteen of 55 genes within the Hox cluster gene regions as differentially expressed in HD, and the Hox genes immediately adjacent to the four Hox cluster miRNAs as up-regulated. Pathway analysis of mRNA targets of these miRNAs implicated functions for neuronal differentiation, neurite outgrowth, cell death and survival. In regression models among the HD brains, huntingtin CAG repeat size, onset age and age at death were independently found to be inversely related to miR-10b-5p levels. CAG repeat size and onset age were independently inversely related to miR-196a-5p, onset age was inversely related to miR-196b-5p and age at death was inversely related to miR-615-3p expression. These results suggest these Hox-related miRNAs may be involved in neuroprotective response in HD. Recently, miRNAs have shown promise as biomarkers for human diseases and given their relationship to disease expression, these miRNAs are biomarker candidates in HD.

Evaluation of Parkinson disease risk variants as expression-QTLs.

The recent Parkinson Disease GWAS Consortium meta-analysis and replication study reports association at several previously confirmed risk loci SNCA, MAPT, GAK/DGKQ, and HLA and identified a novel risk locus at RIT2. To further explore functional consequences of these associations, we investigated modification of gene expression in prefrontal cortex brain samples of pathologically confirmed PD cases (N = 26) and controls (N = 24) by 67 associated SNPs in these 5 loci. Association between the eSNPs and expression was evaluated using a 2-degrees of freedom test of both association and difference in association between cases and controls, adjusted for relevant covariates. SNPs at each of the 5 loci were tested for cis-acting effects on all probes within 250 kb of each locus. Trans-effects of the SNPs on the 39,122 probes passing all QC on the microarray were also examined. From the analysis of cis-acting SNP effects, several SNPs in the MAPT region show significant association to multiple nearby probes, including two strongly correlated probes targeting the gene LOC644246 and the duplicated genes LRRC37A and LRRC37A2, and a third uncorrelated probe targeting the gene DCAKD. Significant cis-associations were also observed between SNPs and two probes targeting genes in the HLA region on chromosome 6. Expanding the association study to examine trans effects revealed an additional 23 SNP-probe associations reaching statistical significance (p<2.8 × 10(-8)) including SNPs from the SNCA, MAPT and RIT2 regions. These findings provide additional context for the interpretation of PD associated SNPs identified in recent GWAS as well as potential insight into the mechanisms underlying the observed SNP associations.

Assessment of cortical and striatal involvement in 523 Huntington disease brains.

OBJECTIVE: To evaluate the relationship of striatal involvement in Huntington disease (HD) to involvement in other brain regions, CAG repeat size, onset age, and other factors. METHODS: We examined patterns of neuropathologic involvement in 664 HD brains submitted to the Harvard Brain Tissue Resource Center. Brains with concomitant Alzheimer or Parkinson changes (n = 82), more than 20% missing data (n = 46), incomplete sample submission (n = 12), or CAG repeat less than 36 (n = 1) were excluded, leaving 523 cases. Standardized ratings from 0 (absent) to 4 (severe) of gross and microscopic involvement were performed for 50 regions. Cluster analysis reduced the data to 2 main measures of involvement: striatal and cortical. RESULTS: The clusters were correlated with each other (r = 0.42) and with disease duration (striatal: r = 0.35; cortical: r = 0.31). The striatal cluster was correlated with HD repeat size (r = 0.50). The cortical cluster showed a stronger correlation with decreased brain weight (r = -0.52) than the striatal cluster (r = -0.33). The striatal cluster was correlated with younger death age (r = -0.31) and onset age (r = -0.46) while the cortical cluster was not (r = 0.09, r = -0.04, respectively). CONCLUSIONS: The 2 brain clusters had different relationships to the HD CAG repeat size, onset age, and brain weight, suggesting that neuropathologic involvement does not proceed in a strictly coupled fashion. The pattern and extent of involvement varies substantially from one brain to the next. These results suggest that regional involvement in HD brain is modified by factors which, if identified, may lend insight into novel routes to therapeutics.

TAA repeat variation in the GRIK2 gene does not influence age at onset in Huntington's disease.

Huntington's disease is a neurodegenerative disorder caused by an expanded CAG trinucleotide repeat whose length is the major determinant of age at onset but remaining variation appears to be due in part to the effect of genetic modifiers. GRIK2, which encodes GluR6, a mediator of excitatory neurotransmission in the brain, has been suggested in several studies to be a modifier gene based upon a 3' untranslated region TAA trinucleotide repeat polymorphism. Prior to investing in detailed studies of the functional impact of this polymorphism, we sought to confirm its effect on age at onset in a much larger dataset than in previous investigations. We genotyped the HD CAG repeat and the GRIK2 TAA repeat in DNA samples from 2,911 Huntington's disease subjects with known age at onset, and tested for a potential modifier effect of GRIK2 using a variety of statistical approaches. Unlike previous reports, we detected no evidence of an influence of the GRIK2 TAA repeat polymorphism on age at motor onset. Similarly, the GRIK2 polymorphism did not show significant modifier effect on psychiatric and cognitive age at onset in HD. Comprehensive analytical methods applied to a much larger sample than in previous studies do not support a role for GRIK2 as a genetic modifier of age at onset of clinical symptoms in Huntington's disease.

Gene expression profiles in Parkinson disease prefrontal cortex implicate FOXO1 and genes under its transcriptional regulation.

Parkinson disease (PD) is a complex neurodegenerative disorder with largely unknown genetic mechanisms. While the degeneration of dopaminergic neurons in PD mainly takes place in the substantia nigra pars compacta (SN) region, other brain areas, including the prefrontal cortex, develop Lewy bodies, the neuropathological hallmark of PD. We generated and analyzed expression data from the prefrontal cortex Brodmann Area 9 (BA9) of 27 PD and 26 control samples using the 44K One-Color Agilent 60-mer Whole Human Genome Microarray. All samples were male, without significant Alzheimer disease pathology and with extensive pathological annotation available. 507 of the 39,122 analyzed expression probes were different between PD and control samples at false discovery rate (FDR) of 5%. One of the genes with significantly increased expression in PD was the forkhead box O1 (FOXO1) transcription factor. Notably, genes carrying the FoxO1 binding site were significantly enriched in the FDR-significant group of genes (177 genes covered by 189 probes), suggesting a role for FoxO1 upstream of the observed expression changes. Single-nucleotide polymorphisms (SNPs) selected from a recent meta-analysis of PD genome-wide association studies (GWAS) were successfully genotyped in 50 out of the 53 microarray brains, allowing a targeted expression-SNP (eSNP) analysis for 52 SNPs associated with PD affection at genome-wide significance and the 189 probes from FoxO1 regulated genes. A significant association was observed between a SNP in the cyclin G associated kinase (GAK) gene and a probe in the spermine oxidase (SMOX) gene. Further examination of the FOXO1 region in a meta-analysis of six available GWAS showed two SNPs significantly associated with age at onset of PD. These results implicate FOXO1 as a PD-relevant gene and warrant further functional analyses of its transcriptional regulatory mechanisms.

Postmortem Interval Influences α-Synuclein Expression in Parkinson Disease Brain.

Duplications and triplications of the α-synuclein (SNCA) gene increase risk for PD, suggesting increased expression levels of the gene to be associated with increased PD risk. However, past SNCA expression studies in brain tissue report inconsistent results. We examined expression of the full-length SNCA transcript (140 amino acid protein isoform), as well as total SNCA mRNA levels in 165 frontal cortex samples (101 PD, 64 control) using quantitative real-time polymerase chain reaction. Additionally, we evaluated the relationship of eight SNPs in both 5' and 3' regions of SNCA with the gene expression levels. The association between postmortem interval (PMI) and SNCA expression was different for PD and control samples: SNCA expression decreased with increasing PMI in cases, while staying relatively constant in controls. For short PMI, SNCA expression was increased in PD relative to control samples, whereas for long PMI, SNCA expression in PD was decreased relative to control samples.