Epidemiology

Background: The recently described interaction between smoking, human leukocyte antigen (HLA) DRB1*15 and absence of HLA-A*02 with regard to multiple sclerosis (MS) risk shows that the risk conveyed by smoking differs depending on genetic background. We aimed to investigate whether a similar interaction exists between passive smoking and HLA genotype. Methods: We used one case-control study with incident cases of MS (736 cases, 1195 controls) and one with prevalent cases (575 cases, 373 controls). Never-smokers with different genotypes and passive smoking status were compared with regard to occurrence of MS, by calculating odds ratios (ORs) with 95% confidence intervals (CIs). The potential interaction between different genotypes and passive smoking was evaluated by calculating the attributable proportion (AP) due to interaction. Results: An interaction was observed between passive smoking and carriage of HLA-DRB1*15 (AP 0.3, 95% CI 0.02-0.5 in the incident study, and AP 0.4, 95% CI 0.1-0.7 in the prevalent study), as well as between passive smoking and absence of HLA-A*02. Compared with non-smokers without any of these two genetic risk factors, non-exposed subjects with the two risk genotypes displayed an OR of 4.5 (95% CI 3.3-6.1) whereas the same genotype for subjects exposed to passive smoking rendered an OR of 7.7 (95% CI 5.5-10.8). Conclusions: The risk of developing MS associated with different HLA genotypes may be influenced by exposure to passive smoking. The finding supports our hypothesis that priming of the immune response in the lungs may subsequently lead to MS in people with a genetic susceptibility to the disease.

Investigating genetic interactions (epistasis) has proven difficult despite the recent advances of both laboratory methods and statistical developments. With no 'best' statistical approach available, combining several analytical methods may be optimal for detecting epistatic interactions. Using a multi-stage analysis that incorporated supervised machine learning and methods of association testing, we investigated epistatic interactions with a well-established genetic factor (PTPN22 1858T) in a complex autoimmune disease (rheumatoid arthritis (RA)). Our analysis consisted of four principal stages: Stage I (data reduction)-identifying candidate chromosomal regions in 292 affected sibling pairs, by predicting PTPN22 concordance using multipoint identity-by-descent probabilities and a supervised machine learning algorithm (Random Forests); Stage II (extension analysis)-testing detailed genetic data within candidate chromosomal regions for epistasis with PTPN22 1858T in 677 cases and 750 controls using logistic regression; Stage III (replication analysis)-confirmation of epistatic interactions in 947 cases and 1756 controls; Stage IV (combined analysis)-a pooled analysis including all 1624 RA cases and 2506 control subjects for final estimates of effect size. A total of seven replicating epistatic interactions were identified. SNP variants within CDH13, MYO3A, CEP72 and near WFDC1 showed significant evidence for interaction with PTPN22, affecting susceptibility to RA.

Using an aquaporin-4 (AQP4) M1-isoform-specific enzyme-linked immunosorbent assay (ELISA) and a fixed transfected cell-based assay (CBA), we tested AQP4-IgG in a northern California population representative cohort of 3293 potential cases with multiple sclerosis (MS). Seropositive cases were tested additionally by fluorescence-activated cell sorting, a live transfected cell-based assay. Sera samples were available in 1040 cases; 7 yielded positive results, 4 by ELISA alone and 3 by both ELISA and CBA. Clinical data (episodes of optic neuritis and longitudinally extensive transverse myelitis [reported on at least 1 magnetic resonance imaging spine]) supported the alternative diagnosis of neuromyelitis optica for 2 patients as seropositive by both ELISA and CBA. These 2 patients alone tested positive by a fluorescence-activated cell-sorting assay. The diagnosis of MS was considered correct in the other 5 patients. Thus, 5 ELISA results and 1 fixed CBA result were false positive. Sensi...

To investigate the association between obesity and multiple sclerosis (MS) while accounting for established genetic and environmental risk factors. Participants included members of Kaiser Permanente Medical Care Plan, Northern California Region (KPNC) (1235 MS cases and 697 controls). Logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (95% CI). Body mass index (BMI) or body size was the primary predictor of each model. Both incident and prevalent MS cases were studied. In analyses stratified by gender, being overweight at ages 10 and 20 were associated with MS in females (p<0.01). Estimates trended in the same direction for males, but were not significant. BMI in 20s demonstrated a linear relationship with MS (p-trend=9.60×10(-4)), and a twofold risk of MS for females with a BMI≥30kg/m(2) was observed (OR=2.15, 95% CI 1.18, 3.92). Significant associations between BMI in 20s and MS in males were not observed. Multivariate modelling dem...

There is a strong and complex genetic component to multiple sclerosis (MS). In addition to variation in the major histocompatibility complex (MHC) region on chromosome 6p21.3, 110 non-MHC susceptibility variants have been identified in Northern Europeans, thus far. The majority of the MS-associated genes are immune related; however, similar to most other complex genetic diseases, the causal variants and biological processes underlying pathogenesis remain largely unknown. We created a comprehensive catalog of putative functional variants that reside within linkage disequilibrium regions of the MS-associated genic variants to guide future studies. Bioinformatics analyses were also conducted using publicly available resources to identify plausible pathological processes relevant to MS and functional hypotheses for established MS-associated variants.

Determine whether MS-specific DNA methylation profiles can be identified in whole blood or purified immune cells from untreated MS patients. Whole blood, CD4+ and CD8+ T cell DNA from 16 female, treatment naïve MS patients and 14 matched controls was profiled using the HumanMethylation450K BeadChip. Genotype data were used to assess genetic homogeneity of our sample and to exclude potential SNP-induced DNA methylation measurement errors. As expected, significant differences between CD4+ T cells, CD8+ T cells and whole blood DNA methylation profiles were observed, regardless of disease status. Strong evidence for hypermethylation of CD8+ T cell, but not CD4+ T cell or whole blood DNA in MS patients compared to controls was observed. Genome-wide significant individual CpG-site DNA methylation differences were not identified. Furthermore, significant differences in gene DNA methylation of 148 established MS-associated risk genes were not observed. While genome-wide significant DNA meth...

Mobile stroke treatment units (MSTUs) with on-site treatment teams that include a vascular neurologist can provide thrombolysis in the prehospital setting faster than treatment in the hospital. These units can be made more resource efficient if the need for an on-site neurologist can be eliminated by relying solely on telemedicine for physician presence. To test whether telemedicine is reliable and remote physician presence is adequate for acute stroke treatment using an MSTU. Prospective observational study conducted between July 18 and November 1, 2014. The dates of the study analysis were November 1, 2014, to March 30, 2015. The setting was a community-based study assessing telemedicine success of the MSTU in Cleveland, Ohio. Participants were the first 100 residents of Cleveland who had an acute onset of stroke-like symptoms between 8 am and 8 pm and were evaluated by the MSTU after the implementation of the MSTU program at the Cleveland Clinic. A vascular neurologist evaluated ...

Comparing the relative fit of competing models can be used to address many different scientific questions. In classical statistics one can, if appropriate, use likelihood ratio tests and information based criterion, whereas clinical medicine has tended to rely on comparisons of fit metrics like C-statistics. However, for many data adaptive modelling procedures such approaches are not suitable. In these cases, statisticians have used cross-validation, which can make inference challenging. In this paper we propose a general approach that focuses on the “conditional” risk difference (conditional on the model fits being fixed) for the improvement in prediction risk. Specifically, we derive a Wald-type test statistic and associated confidence intervals for cross-validated test sets utilizing the independent validation within cross-validation in conjunction with a test for multiple comparisons. We show that this test maintains proper Type I Error under the null fit, and can be used as a g...

Objective: We investigated the association between 52 risk variants identified through genomewide association studies and disease severity in multiple sclerosis (MS). Methods: Ten unique MS case data sets were analyzed. The Multiple Sclerosis Severity Score (MSSS) was calculated using the Expanded Disability Status Scale at study entry and disease duration. MSSS was considered as a continuous variable and as 2 dichotomous variables (median and extreme ends; MSSS of #5 vs .5 and MSSS of ,2.5 vs $7.5, respectively). Single nucleotide polymorphisms (SNPs) were examined individually and as both combined weighted genetic risk score (wGRS) and unweighted genetic risk score (GRS) for association with disease severity. Random-effects meta-analyses were conducted and adjusted for cohort, sex, age at onset, and HLA-DRB1*15:01. Results: A total of 7,125 MS cases were analyzed. The wGRS and GRS were not strongly associated with disease severity after accounting for cohort, sex, age at onset, and HLA-DRB1*15:01. After restricting analyses to cases with disease duration $10 years, associations were null (p value $0.05). No SNP was associated with disease severity after adjusting for multiple testing. Conclusions: The largest meta-analysis of established MS genetic risk variants and disease severity, to date, was performed. Results suggest that the investigated MS genetic risk variants are not associated with MSSS, even after controlling for potential confounders. Further research in large cohorts is needed to identify genetic determinants of disease severity using sensitive clinical and MRI measures, which are critical to understanding disease mechanisms and guiding development of effective treatments.

BACKGROUND-Trajectories of depression over time may be heterogeneous in Multiple Sclerosis (MS) patients. Describing these trajectories will help clinicians understand better the progression of depression in MS patients to aid in patient care decisions. METHODS-Latent class growth analysis (LCGA) was applied to 3,507 MS patients using an electronic health records (EHR) data base to identify subgroups of MS patients based on selfreported depression screening (PHQ-9). Latent trajectory classes were used for group comparisons based on baseline clinical characteristics. RESULTS-Three subgroups were found characterized by high (10.0% [of participants]), wavering above and below moderate (26.2%) and low and variable (63.8%) depression level trajectories. The subpopulation trajectories, respectively, were also characterized by high, moderate and low MS disability at baseline. In contrast, the overall average trajectory was slightly declining and below the moderate depression threshold. CONCLUSION-The LCGA approach described in this paper and applied to MS patients provides a template for improved use of an EHR data base for understanding heterogeneous Contact information

Cognitive impairment is common in multiple sclerosis (MS), and affects employment and quality of life. Large studies are needed to identify risk factors for cognitive decline. Currently, a MS-validated remote assessment for cognitive function does not exist. Studies to determine feasibility of large remote cognitive function investigations in MS have not been published. To determine whether MS patients would participate in remote cognitive studies. We utilized the Modified Telephone Interview for Cognitive Status (TICS-M), a previously validated phone assessment for cognitive function in healthy elderly populations to detect mild cognitive impairment. We identified factors that influenced participation rates. We investigated the relationship between MS risk factors and TICS-M score in cases, and score differences between cases and control individuals. The TICS-M was administered to MS cases and controls. Linear and logistic regression models were utilized. 11.5% of eligible study pa...

The impact of underlying immune-mediated inflammatory diseases (IMID) in patients undergoing hematopoietic stem cell transplant (HSCT) is unclear. Hematopoietic cell transplantation co-morbidity index (HCT-CI) is gaining acceptance as a reliable clinical method to score pre-transplant co-morbidities. Higher HCT-CI from a co-morbid IMID implies higher NRM. However, HCT-CI integrates many IMIDs with different pathogenesis and treatment together which may lead to spurious results. We performed a cross-sectional study using Nationwide Inpatient Sample dataset from 1998 to 2011 to compare the outcomes of HSCT in patients with different co-morbid IMIDs with patients without any co-morbid IMIDs. In both our multivariate and stringent matched-pair analysis, ulcerative colitis (UC) was associated with increased mortality while rheumatoid arthritis and psoriasis were associated with lower mortality as compared to no IMID group. Furthermore, in allogeneic HSCT subgroup, UC was associated with ...

Background/objective: In 2019, the 2010 U.S. multiple sclerosis (MS) prevalence was robustly estimated (265.1–309.2/100,000) based on large administrative health-claims datasets. Using 56.6 million electronic health records (EHRs), we sought to generate complementary age, sex, and race standardized estimates. Methods/results: Using de-identified EHRs and 2018 U.S. Census data, we estimated an age- and sex-standardized MS prevalence of 219.5/100,000 which increased to 274.5/100,000 when accounting for White and Black race alone. Women aged 50 to 69 years had the highest prevalence (>600/100,000). Among White and Black Americans, the age- and sex-standardized prevalence was 283.7 and 226.1 per 100,000, respectively. Conclusion: Using 56.6 million EHRs and standardizing for age, sex, and race (White and Black Americans only), we estimated at least 810,504 Americans were living with MS in 2018.

Aim: There are limited data on psychological outcomes in older people with epilepsy (PWE). This analysis, from a large pooled dataset of clinical studies from the Managing Epilepsy Well (MEW) Network, examined clinical variables including depressive symptom severity, quality of life and epilepsy self-management competency among older (age 55+) vs younger (<age 55) PWE. We were particularly interested in differences between older vs younger individuals with clinically significant depression. Methods: Analyses used baseline data from 9 MEW Network studies and examined demographic and clinical variables. Older vs younger individuals were compared and then we assessed groups with clinically significant depression vs those without clinically significant depression using the PHQ-9 and QOLIE-10 as a measure of quality of life. Results: The sample included 935 individuals. Compared to younger adults (n=774), the older group (n=161) had a better quality of life (p= 0.041) and more individuals without clinically significant depression (p=0.038). There was a trend for slightly lower depression severity scores (PHQ-9 total) (p=0.07) in the older group and a trend for fewer seizures (p=0.055) in older adults relative to younger adults. Conclusion: Compared to younger PWE, older PWE have less clinically significant depression and better quality of life. Future research needs to identify possible mechanisms underlying these differences.

Background and Purpose Epilepsy is often associated with substantial stigma. This study evaluated clinical correlates of stigma in a sample of people living with epilepsy (PLWE) considered high risk due to frequent seizures or other negative health events. Methods Data were derived from an epilepsy self-management clinical trial. Standardized measures assessed socio-demographics, epilepsy stigma, epilepsy severity, self-efficacy, selfmanagement competency, health literacy, depressive symptoms severity, functional status, social support and quality of life. Results There were 120 individuals, mean age of 41.73 (SD=17.08), 81 men (66.9%), and 79 (65.3%) African-American. Individual factors correlated with worse stigma w ere indicative of more severe or poorly controlled seizures (frequent seizures, worse seizure severity scores, more antiepileptic drugs), mental health comorbidity (worse depression severity, other comorbidities) and factors related to individual functioning and perceived competency in managing their health (health literacy, health functioning, self-efficacy, quality of life). Multivariable linear regression found that worse quality of life, and having a mental condition were associated with more stigma (β=6.4 and 6.8, respectively), while higher self-efficacy, health literacy and social support were associated with less stigma (β=-0.06,-2.1, and-0.3, respectively). These five variables explained 50% of stigma variation. Conclusions Stigma burden can be substantial among PLWE and may vary depending on contextual factors such as mental health comorbidity. Care approaches that screen for psychiatric comorbidities, address low health literacy, institute promising self-management programs, and employ effective health communication strategies about epilepsy misconceptions, may reduce epilepsy related burden.

Background: The incidence of acute lymphoblastic leukemia (ALL) is nearly 20% higher among Hispanics than non-Hispanic Whites. Previous studies have shown evidence for association between risk of ALL and variation within IKZF1, ARID5B, CEBPE, CDKN2A, GATA3, and BM1-PIP4K2A genes. However, variants identified only account for &lt;10% of the genetic risk of ALL. Methods: We applied pathway-based analyses to genome-wide association study (GWAS) data from the California Childhood Leukemia Study to determine whether different biologic pathways were overrepresented in childhood ALL and major ALL subtypes. Furthermore, we applied causal inference and data reduction methods to prioritize candidate genes within each identified overrepresented pathway, while accounting for correlation among SNPs. Results: Pathway analysis results indicate that different ALL subtypes may involve distinct biologic mechanisms. Focal adhesion is a shared mechanism across the different disease subtypes. For ALL, t...