Coombes, Brandon J.

Background: Risk for venous thromboembolism has a strong genetic component. Whole genome sequencing from the TOPMed program (Trans-Omics for Precision Medicine) allowed us to look for new associations, particularly rare variants missed by standard genome-wide association studies. Methods: The 3793 cases and 7834 controls (11.6% of cases were individuals of African, Hispanic/Latino, or Asian ancestry) were analyzed using a single variant approach and an aggregate gene-based approach using our primary filter (included only loss-of-function and missense variants predicted to be deleterious) and our secondary filter (included all missense variants). Results: Single variant analyses identified associations at 5 known loci. Aggregate gene-based analyses identified only PROC (odds ratio, 6.2 for carriers of rare variants; P =7.4×10 −14 ) when using our primary filter. Employing our secondary variant filter led to a smaller effect size at PROC (odds ratio, 3.8; P =1.6×10 −14 ), while excluding variants found only in rare isoforms led to a larger one (odds ratio, 7.5). Different filtering strategies improved the signal for 2 other known genes: PROS1 became significant (minimum P =1.8×10 −6 with the secondary filter), while SERPINC1 did not (minimum P =4.4×10 −5 with minor allele frequency <0.0005). Results were largely the same when restricting the analyses to include only unprovoked cases; however, one novel gene, MS4A1 , became significant ( P =4.4×10 −7 using all missense variants with minor allele frequency <0.0005). Conclusions: Here, we have demonstrated the importance of using multiple variant filtering strategies, as we detected additional genes when filtering variants based on their predicted deleteriousness, frequency, and presence on the most expressed isoforms. Our primary analyses did not identify new candidate loci; thus larger follow-up studies are needed to replicate the novel MS4A1 locus and to identify additional rare variation associated with venous thromboembolism.

AbstractTo date, bipolar disorder (BD) genetic studies and polygenic risk scores (PRSs) for BD are based primarily on populations of European descent (EUR) and lack representation from other ancestries including Latin American (LAT). Here, we describe a new LAT cohort from the Mayo Clinic Bipolar Biobank (MCBB), a multisite collaboration with recruitment sites in the United States (EUR; 1,443 cases and 777 controls) and Mexico and Chile (LAT; 211 cases and 161 controls) and use the sample to explore the performance of a BD‐PRS in a LAT population. Using results from the largest genome‐wide association study of BD in EUR individuals, PRSice2 and LDpred2 were used to compute BD‐PRSs in the LAT and EUR samples from the MCBB. PRSs explained up to 1.4% (PRSice) and 4% (LDpred2) of the phenotypic variance on the liability scale in the LAT sample compared to 3.8% (PRSice2) and 3.4% (LDpred2) in the EUR samples. Future larger studies should further explore the differential performance of different PRS approaches across ancestries. International multisite studies, such as this one, have the potential to address diversity‐related limitations of prior genomic studies and ultimately contribute to the reduction of health disparities.

Lithium has been a cornerstone treatment for bipolar disorder (BD). Despite descriptions in the literature regarding associations between long-term lithium therapy (LTLT) and development of a thyroid disorder (overt/subclinical hypo/hyperthyroidism, thyroid nodule, and goiter) in BD, factors such as time to onset of thyroid abnormalities and impact on clinical outcomes in the course of illness have not been fully characterized. In this study we aimed to compare clinical characteristics of adult BD patients with and without thyroid disorders who were on LTLT. We aimed to identify the incidence of thyroid disorders in patients with BD on LTLT and response to lithium between patients with and without thyroid disorders in BD. The Cox proportional model was used to find the median time to the development of a thyroid disorder. Our results showed that up to 32% of patients with BD on LTLT developed a thyroid disorder, of which 79% developed hypothyroidism, which was corrected with thyroid hormone replacement. We did not find significant differences in lithium response between patients with or without thyroid disorders in BD. Findings from this study suggest that patients with BD and comorbid thyroid disorders when adequately treated have a response to lithium similar to patients with BD and no thyroid disorders.

AbstractBackgroundIn the Alzheimer’s disease sequencing project (ADSP) whole exome dataset, only the well‐known TREM2.pR47H variant shows genome‐wide significance by conventional single variant analysis. To identify novel AD genes related to TREM2, we used gene‐based polygenic score analysis (PGSA) to evaluate an immune, temporal cortical co‐expression network with 229 genes including TREM2.MethodThe most recent whole exome variant call files from the ADSP (NG00067.v7) were subjected to stringent quality control. Post‐QC samples were divided into discovery (4174 samples sequenced at Broad), test (3299 samples sequenced at WashU), and follow‐up (2273 samples sequenced at Baylor) sets. The pruned variants (r2 < 0.2) with a minor allele count over 20 in each gene were analyzed by Broad/WashU PGSA thereby obtaining P‐values (gPbr.wa) for each gene in WashU samples. To assess significance in independent Baylor samples, cumulative Broad/Baylor PGSA was performed using a novel approach in which variants were stratified by both gene (gPbr.wa) and variant (Broad.P).ResultAfter excluding TREM2, the five variants with gPbr.wa ≤ 0.08 and Broad.P ≤ 0.03 showed significant association in Broad/Baylor PGSA. One of these variants showed no evidence of association with AD in the combined dataset. Polygenic scores for the other four variants, which were in three genes, showed significant association in Baylor samples, and significant, essentially identical association in WashU samples. Polygenic scores for nine additional variants in these genes (0.03> Broad.P ≤ 0.13) also showed significant, essentially identical association in Baylor and WashU samples. The association of these 13 variants with AD was driven primarily by six deleterious, protein‐altering variants with minor allele frequencies less than 1%, but the other 7 variants also contributed.ConclusionUsing gene‐based polygenic score analysis to analyze an immune co‐expression network, we identify three novel immune genes with actionable nonsynonymous and stopgain variants that show significant, replicable association with AD in the most recent release of the ADSP whole exome dataset.

AbstractBackground and ObjectivesSubstance use disorders (SUDs) are chronic relapsing diseases characterized by significant morbidity and mortality. Phenomenologically, patients with SUDs present with a repeating cycle of intoxication, withdrawal, and craving, significantly impacting their diagnosis and treatment. There is a need for better identification and monitoring of these disease states. Remote monitoring chronic illness with wearable devices offers a passive, unobtrusive, constant physiological data assessment. We evaluate the current evidence base for remote monitoring of nonalcohol, nonnicotine SUDs.MethodsWe performed a systematic, comprehensive literature review and screened 1942 papers.ResultsWe found 15 studies that focused mainly on the intoxication stage of SUD. These studies used wearable sensors measuring several physiological parameters (ECG, HR, O2, Accelerometer, EDA, temperature) and implemented study‐specific algorithms to evaluate the data.Discussion and ConclusionsStudies were extracted, organized, and analyzed based on the three SUD disease states. The sample sizes were relatively small, focused primarily on the intoxication stage, had low monitoring compliance, and required significant computational power preventing “real‐time” results. Cardiovascular data was the most consistently valuable data in the predictive algorithms. This review demonstrates that there is currently insufficient evidence to support remote monitoring of SUDs through wearable devices.Scientific SignificanceThis is the first systematic review to show the available data on wearable remote monitoring of SUD symptoms in each stage of the disease cycle. This clinically relevant approach demonstrates what we know and do not know about the remote monitoring of SUDs within disease states.

Abstract Background: Alterations in innate immunity are pathologically associated with and genetically implicated in Alzheimer’s disease (AD). In the whole exome sequence (WES) dataset generated by the Alzheimer’s Disease Sequencing Project (ADSP), only the previously identified p.R47H variant in the innate immunity gene, TREM2, shows study-wide association with risk of AD. Using a novel approach, we searched the ADSP WES data to identify additional immune pathway genes with deleterious variants that, like TREM2.pR47H, show strong association with AD. Methods: Using polygenic risk scores (PRS) to analyze association with AD, we evaluated deleterious variants (CADD Phred-scaled score > 20) with a minor allele count of 20 or more in 228 genes comprising an immune co-expression network containing TREM2 (CENTREM2). A significant polygenic component composed of deleterious stop-gain and non-synonymous variants was identified, and false discovery rates were determined for the variants in this component. In genes harboring a significant variant, PRS for all variants in the genes were then analyzed. Results: The PRS for the 182 deleterious variants in CENTREM2 showed significant association with AD that was driven by 142 deleterious variants (136 non-synonymous, 6 stop-gain). In the 142 variant polygenic component, four variants had significant AD risk association: TREM2.pR47H, two deleterious stop-gain variants (FCGR1A.pR92X, and LILRB1.pY331X) in novel AD genes and 1 non-synonymous variant (ATP8B4.pG395S). Remarkably, PRS for the 36 additional variants in these four genes also showed significant association with AD. The PRS for all 40 variants in the 4 genes, showed significant, replicable association with AD and 3 additional variants in this polygenic component had significant false discovery rates: ATP8B4.pR1059Q, LILRB1.pP7P, and LILRB1.pY327Y. Conclusions: Here, we identify 3 immune pathway genes (ATP8B4, LILRB1, and FCGR1A) with a variant that associates with AD. Like TREM2.pR47H, each of the variants has a minor allele frequency less than 1% and is a deleterious, protein altering variant with a strong effect that increases or decreases (LILRB1.pY331X) risk of AD. Additional variants in these genes also alter risk of AD. The variants identified here are ideally suited for studies aimed at understanding how the innate immune system may be modulated to alter risk of AD.

Abstract Background Decreasing pain catastrophizing and improving self-efficacy to self-manage chronic pain symptoms are important treatment targets in the context of interdisciplinary pain rehabilitation. Greater pain catastrophizing has been shown to be associated with greater impact of pain symptoms on functioning; conversely, greater pain self-efficacy has been associated with lower pain intensity and lower levels of disability. Objective To prospectively evaluate interdisciplinary pain rehabilitation outcomes, as well as to evaluate the mediating effects of both pain catastrophizing and pain self-efficacy on outcome. Methods Participants were 315 patients with chronic pain between April 2017 and April 2018 who completed a 3-week interdisciplinary pain rehabilitation program. Pain severity, pain interference, pain catastrophizing, pain self-efficacy, quality of life, depressive symptom questionnaires, and measures of physical performance were assessed before and after treatment. Follow-up questionnaires were returned by 163 participants. Effect size and reliable change analyses were conducted from pre- to posttreatment and from pretreatment to 6-month follow-up. Mediation analyses were conducted to determine the mediating effect of pain catastrophizing and pain self-efficacy on pain outcome. Results Significant improvements from pre- to posttreatment in pain outcomes were observed, and more than 80% evidenced a reliable change in at least one pain-relevant measure. Pain catastrophizing and pain self-efficacy mediated the relationship between changes in pain outcomes. Conclusions Interdisciplinary pain rehabilitation is an effective treatment, and decreasing pain catastrophizing and increasing pain self-efficacy can influence maintenance of treatment gains.

Background: The Trans-Omics for Precision Medicine (TOPMed) program is performing whole-genome sequencing across multiple studies, including longitudinal cohorts, case-control, and case-only sample sets. Detecting the effects of low frequency variants requires large sample sizes, which can only be achieved by combining data across diverse study designs, including matching of case-only sample sets with controls from other studies. Here we present a strategy for combined analysis of venous thromboembolism (VTE) case status in 3 longitudinal cohorts and 3 case-only sample sets, in the context of whole-genome association studies. Methods: For each cohort study, we sampled ‘pure’ controls (without replacement) from the risk set of each incident case, within strata defined by sex, ancestry and birth-cohort. Pure controls had no event throughout their period of observation. A case’s risk set was defined as controls with no prior VTE history and under observation through an age at least as old as the case. For case-only sample sets, controls for each case were sampled from a cohort study, using the same risk set definition. Because of limited overlap in birth years between the cohort studies and the case-only sample sets, this matching was done within strata defined only by sex and ancestry group. Mixed model logistic regression will be used to account for relatedness as a random effect. Although conditional logistic regression is not practical for whole-genome association studies, case-control matching is implicitly recognized by a fixed effect for age-at-event for each matched set (1 case and >=1 matched controls). Additional fixed effects will include sample set and sex. We will also adjust for variations in case-control ratio among the matched sets. Results: In two cohort studies, we matched 1,231 cases to 4,820 controls (overall ratio = 1:3.9); only 500 controls and 5 cases could not be matched. For the case-only sample sets we matched 2,141 cases to 2,780 controls from one cohort study (overall ratio = 1:1.3); zero controls and only 14 cases could not be matched. Conclusions: We were successfully able to match nearly all cases to controls, and more than 90% of controls were also matched. By matching controls to cases based on age at event, we can account for the different risk of VTE by age clusters. Although this strategy does not provide an asymptotically unbiased estimated of the hazard ratio, compared to classical risk set sampling, it uses a large portion of the available data, it provides odds ratio estimates yielding the correct sign of association, and it reduces the potential influence of resampling subjects with rare variants. This strategy also enables combined analysis of multiple studies with different designs.

Abstract Introduction Sleep disruption is common in patients with alcohol use disorders (AUD) and major depressive disorders (MDD). Our understanding of the differences in the rates of sleep disturbance and overall sleep duration in patients with AUD, MDD, and comorbid AUD and MDD is limited. Furthermore, it is unknown whether there is variation in demographic and clinical characteristics associated with sleep disturbance and duration in these diagnostic groups. Methods This study utilized data from the UK Biobank (UKB). Depression status was determined based on review of International Classification of Diseases (ICD) codes and health records. AUD status was based on AUDIT scores (score ≥8 was defined as AUD) and sleep disturbance was evaluated utilizing a self-reported questionnaire. The sample was categorized into those with MDD alone (MDD+/AUD-)(n=18,154), AUD alone (MDD-/AUD+)(n=6123), both (MDD+/AUD+)(n=9027), and controls with neither (MDD-/AUD-)(n=27,573). We used generalized linear models (GLMs) to compare rates of sleep disruption and duration among the groups and determine the clinical predictors of sleep disturbance/duration in the four groups as well as test whether these factors differed among the groups. Results The prevalence of sleep disturbance in the control sample (MDD-/AUD-) was 26.4% and the self-reported sleep duration in this sample was 7.209±0.919. Subjects with AUD and/or MDD had greater rates of sleep disturbance and shorter sleep duration. Among the different diagnostic categories, the prevalence of sleep disturbance was highest in subjects with MDD+/AUD+ (36.5%) followed by those with MDD+/AUD- (35.6%) and MDD-/AUD+ (27.9%)(all p&lt;0.0001). Similarly, the sleep duration was shortest in subjects with MDD+/AUD+ (7.143±1.016), followed by MDD+/AUD- (7.158±1.050) and by MDD-/AUD+ (7.202±0.891)(all p&lt;0.0001). Subjects with sleep disturbance were more likely to be older, female, and with higher body mass index, Townsend deprivation index, and neuroticism scores across all four groups (all p&lt;0.05). Conclusion In a large population-based cohort, MDD with and without comorbid AUD was associated with greater rates of sleep disturbance and shorter sleep duration than AUD alone. The clinical and demographic factors associated with sleep disturbance did not differ in these diagnostic categories, indicating possible similar underlying risk factors. Support (if any) NA