Metformin Cessation and Dementia Incidence.

Importance: Prior studies suggested that metformin may be associated with reduced dementia incidence, but associations may be confounded by disease severity and prescribing trends. Cessation of metformin therapy in people with diabetes typically occurs due to signs of kidney dysfunction but sometimes is due to less serious adverse effects associated with metformin. Objective: To investigate the association of terminating metformin treatment for reasons unrelated to kidney dysfunction with dementia incidence. Design, Setting, and Participants: This cohort study was conducted at Kaiser Permanente Northern California, a large integrated health care delivery system, among a cohort of metformin users born prior to 1955 without history of diagnosed kidney disease at metformin initiation. Dementia follow-up began with the implementation of electronic health records in 1996 and continued to 2020. Data were analyzed from November 2021 through September 2023. Exposures: A total of 12 220 early terminators, individuals who stopped metformin with normal estimated glomerular filtration rate (eGFR), were compared with routine metformin users, who had not yet terminated metformin treatment or had terminated (with or without restarting) after their first abnormal eGFR measurement. Early terminators were matched with routine users of the same age and gender who had diabetes for the same duration. Main outcomes and measures: The outcome of interest was all-cause incident dementia. Follow-up for early terminators and their matched routine users was started at age of termination for the early terminator. Survival models adjusted for sociodemographic characteristics and comorbidities at the time of metformin termination (or matched age). Mediation models with HbA1c level and insulin usage 1 and 5 years after termination tested whether changes in blood glucose or insulin usage explained associations between early termination of metformin and dementia incidence. Results: The final analytic sample consisted of 12 220 early terminators (5640 women [46.2%]; mean [SD] age at start of first metformin prescription, 59.4 [9.0] years) and 29 126 routine users (13 582 women [46.6%]; mean [SD] age at start of first metformin prescription, 61.1 [8.9] years). Early terminators had 1.21 times the hazard of dementia diagnosis compared with routine users (hazard ratio, 1.21; 95% CI, 1.12 to 1.30). In mediation analysis, contributions to this association by changes in HbA1c level or insulin use ranged from no contribution (0.00 years; 95% CI, -0.02 to 0.02 years) for insulin use at 5 years after termination to 0.07 years (95% CI, 0.02 to 0.13 years) for HbA1c level at 1 year after termination, suggesting that the association was largely independent of changes in HbA1c level and insulin usage. Conclusions and Relevance: In this study, terminating metformin treatment was associated with increased dementia incidence. This finding may have important implications for clinical treatment of adults with diabetes and provides additional evidence that metformin is associated with reduced dementia risk.

Low- and High-Density Lipoprotein Cholesterol and Dementia Risk Over 17 Years of Follow-up Among Members of a Large Health Care Plan.

BACKGROUND AND OBJECTIVES: The associations of high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) with dementia risk in later life may be complex, and few studies have sufficient data to model nonlinearities or adequately adjust for statin use. We evaluated the observational associations of HDL-C and LDL-C with incident dementia in a large and well-characterized cohort with linked survey and electronic health record (EHR) data. METHODS: Kaiser Permanente Northern California health plan members aged 55 years and older who completed a health behavior survey between 2002 and 2007, had no history of dementia before the survey, and had laboratory measurements of cholesterol within 2 years after survey completion were followed up through December 2020 for incident dementia (Alzheimer disease-related dementia [ADRD]; Alzheimer disease, vascular dementia, and/or nonspecific dementia) based on ICD-9 or ICD-10 codes in EHRs. We used Cox models for incident dementia with follow-up time beginning 2 years postsurvey (after cholesterol measurement) and censoring at end of membership, death, or end of study period. We evaluated nonlinearities using B-splines, adjusted for demographic, clinical, and survey confounders, and tested for effect modification by baseline age or prior statin use. RESULTS: A total of 184,367 participants [mean age at survey = 69.5 years, mean HDL-C = 53.7 mg/dL (SD = 15.0), mean LDL-C = 108 mg/dL (SD = 30.6)] were included. Higher and lower HDL-C values were associated with elevated ADRD risk compared with the middle quantile: HDL-C in the lowest quintile was associated with an HR of 1.07 (95% CI 1.03-1.11), and HDL-C in the highest quintile was associated with an HR of 1.15 (95% CI 1.11-1.20). LDL-C was not associated with dementia risk overall, but statin use qualitatively modified the association. Higher LDL-C was associated with a slightly greater risk of ADRD for statin users (53% of the sample, HR per 10 mg/dL increase = 1.01, 95% CI 1.01-1.02) and a lower risk for nonusers (HR per 10 mg/dL increase = 0.98; 95% CI 0.97-0.99). There was evidence for effect modification by age with linear HDL-C (p = 0.003) but not LDL-C (p = 0.59). DISCUSSION: Both low and high levels of HDL-C were associated with elevated dementia risk. The association between LDL-C and dementia risk was modest.

Adverse childhood experiences in early life increase the odds of depression among adults with multiple sclerosis.

Background: Adverse childhood experiences are demonstrated risk factors for depression, a common co-morbidity of multiple sclerosis, but are understudied among people with multiple sclerosis. Objective: Estimate the association between adverse childhood experiences and depression among 1,990 adults with multiple sclerosis. Methods: Participants were members of Kaiser Permanente Northern California from two studies between 2006 and 2021 and were diagnosed with multiple sclerosis by a neurologist. Adverse childhood experiences were assessed using two instruments, including the Behavioral Risk Factor Surveillance System. Participants self-reported ever experiencing a major depressive episode. Meta-analysis random effects models and logistic regression were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) to assess the relationship between adverse childhood experiences and a history of depression across study samples. Adverse childhood experiences were expressed as any/none, individual events, and counts. Models adjusted for sex, birth year, race, and ethnicity. Results: Exposure to any adverse childhood experiences increased the odds of depression in people with multiple sclerosis (OR: 1.71, 95% CI: 1.21-2.42). Several individual adverse childhood experiences were also strongly associated with depression, including "significant abuse or neglect" (OR: 2.79, 95% CI: 2.11-3.68). Conclusion: Findings suggest that adverse childhood experiences are associated with depression among people with multiple sclerosis. Screening for depression should be done regularly, especially among people with multiple sclerosis with a history of adverse childhood experiences.

Cross-Trait Mendelian Randomization Study to Investigate Whether Migraine Is a Risk Factor for Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: Migraine is common among people with multiple sclerosis (MS), but the reasons for this are unknown. We tested 3 hypothesized mechanisms for this observed comorbidity, including migraine is a risk factor of MS, genetic variants are shared between the conditions, and migraine is because of MS. METHODS: Data were from 2 sources: publicly available summary statistics from genome-wide association studies of MS (N = 115,748) and migraine (N = 375,752 and N = 361,141) and a case-control study of MS recruited from the Kaiser Permanente Northern California Health Plan (N = 1,991). For the latter participants, migraine status was ascertained using a validated electronic health record migraine probability algorithm or self-report. Using the public summary statistics, we used 2-sample Mendelian randomization to test whether a migraine genetic instrumental variable was associated with MS. We used linkage disequilibrium score regression and LOGODetect to ascertain whether MS and migraine shared genetic variants across the genome and regionally. Using the Northern California MS cohort, we used logistic regression to identify whether people with both MS and migraine had different odds of clinical characteristics (e.g., age at MS onset, Perceived Deficits Questionnaire, and depression) or MS-specific risk factors (e.g., body mass index, smoking status, and infectious mononucleosis status) compared with people with MS without migraine. RESULTS: We did not find evidence supporting migraine as a causal risk factor of MS (p = 0.29). We did, however, identify 4 major histocompatibility complex (MHC) loci shared between MS and migraine. Among the Northern California MS cohort, 774 (39%) experienced migraine. People with both MS and migraine from this cohort were more likely to ever smoke (odds ratio [OR] = 1.30, 95% CI: 1.08-1.57), have worse self-reported cognitive deficits (OR = 1.04, 95% CI: 1.02-1.06), and ever experience depression (OR = 1.48, 95% CI: 1.22-1.80). DISCUSSION: Our findings do not support migraine as a causal risk factor of MS. Several genetic variants, particularly in the MHC, may account for some of the overlap. It seems likely that migraine within the context of MS is because of MS. Identifying what increases the risk of migraine within MS might lead to an improved treatment and quality of life.

Validation of Hindi version of the obstetric quality of recovery score-11 (ObsQoR-11 H) following elective caesarean section.

Background and Aims: Obstetric quality of recovery score-11 (ObsQoR-11) was developed in English to evaluate the quality of recovery in the caesarean section. We aimed to validate the Hindi version of ObsQoR-11 (ObsQoR-11H) for Hindi-speaking patients to evaluate the quality of recovery following the elective caesarean section. Methods: The ObsQoR-11 was translated into Hindi and assessed for validity, acceptability and feasibility. The questionnaire was administered postoperatively at 24 and 48 hours, and the Global Health Numeric Rating Scale (NRS) was used to evaluate recovery. Results: The mean (standard deviation [SD]) (95% confidence interval [CI]) ObsQoR-11 H was 75.94 (4.09)(95% CI 75.1, 76.7) and 80.25 (4.08)(95% CI 79.5, 81) at 24 and 48 hours, respectively. The mean (SD) (95%CI) Global Health NRS scores were 71.22 (5.97)(95% CI 70, 72.4) and 77.37 (5.79)(95% CI 76.2, 78.5) at 24 and 48 hours, respectively. Convergent validity showed a strong correlation between ObsQoR-11H and Global Health NRS (Spearman's correlation coefficient [rs] >0.8 and 0.78) scores at 24 and 48 hours, respectively. Discriminant validity was significant in appreciating the difference between good and poor recovery (P < 0.001). Split-half coefficient of 0.69 and 0.65 and Cronbach's alpha (α) of 0.91 and 0.82 at 24 and 48 hours suggested good score reliability. The acceptability and feasibility of the score were also good. Conclusion: The ObsQoR-11H discriminated well between 'good' and 'poor' recovery and correlated strongly with Global Health NRS scores. It was found to be a valid, reliable, acceptable and feasible tool for psychometric recovery evaluation after elective caesarean section in Hindi-speaking women.

Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network.

BACKGROUND: Genetic studies require precise phenotype definitions, but electronic medical record (EMR) phenotype data are recorded inconsistently and in a variety of formats. OBJECTIVE: To present lessons learned about validation of EMR-based phenotypes from the Electronic Medical Records and Genomics (eMERGE) studies. MATERIALS AND METHODS: The eMERGE network created and validated 13 EMR-derived phenotype algorithms. Network sites are Group Health, Marshfield Clinic, Mayo Clinic, Northwestern University, and Vanderbilt University. RESULTS: By validating EMR-derived phenotypes we learned that: (1) multisite validation improves phenotype algorithm accuracy; (2) targets for validation should be carefully considered and defined; (3) specifying time frames for review of variables eases validation time and improves accuracy; (4) using repeated measures requires defining the relevant time period and specifying the most meaningful value to be studied; (5) patient movement in and out of the health plan (transience) can result in incomplete or fragmented data; (6) the review scope should be defined carefully; (7) particular care is required in combining EMR and research data; (8) medication data can be assessed using claims, medications dispensed, or medications prescribed; (9) algorithm development and validation work best as an iterative process; and (10) validation by content experts or structured chart review can provide accurate results. CONCLUSIONS: Despite the diverse structure of the five EMRs of the eMERGE sites, we developed, validated, and successfully deployed 13 electronic phenotype algorithms. Validation is a worthwhile process that not only measures phenotype performance but also strengthens phenotype algorithm definitions and enhances their inter-institutional sharing.

nuScore: a web-interface for nucleosome positioning predictions.

UNLABELLED: Sequence-directed mapping of nucleosome positions is of major biological interest. Here, we present a web-interface for estimation of the affinity of the histone core to DNA and prediction of nucleosome arrangement on a given sequence. Our approach is based on assessment of the energy cost of imposing the deformations required to wrap DNA around the histone surface. The interface allows the user to specify a number of options such as selecting from several structural templates for threading calculations and adding random sequences to the analysis. AVAILABILITY: The nuScore interface is freely available for use at http://compbio.med.harvard.edu/nuScore. CONTACT: peter_park@harvard.edu; tolstorukov@gmail.com SUPPLEMENTARY INFORMATION: The site contains user manual, description of the methodology and examples.

CGHweb: a tool for comparing DNA copy number segmentations from multiple algorithms.

UNLABELLED: Accurate estimation of DNA copy numbers from array comparative genomic hybridization (CGH) data is important for characterizing the cancer genome. An important part of this process is the segmentation of the log-ratios between the sample and control DNA along the chromosome into regions of different copy numbers. However, multiple algorithms are available in the literature for this procedure and the results can vary substantially among these. Thus, a visualization tool that can display the segmented profiles from a number of methods can be helpful to the biologist or the clinician to ascertain that a feature of interest did not arise as an artifact of the algorithm. Such a tool also allows the methodologist to easily contrast his method against others. We developed a web-based tool that applies a number of popular algorithms to a single array CGH profile entered by the user. It generates a heatmap panel of the segmented profiles for each method as well as a consensus profile. The clickable heatmap can be moved along the chromosome and zoomed in or out. It also displays the time that each algorithm took and provides numerical values of the segmented profiles for download. The web interface calls algorithms written in the statistical language R. We encourage developers of new algorithms to submit their routines to be incorporated into the website. AVAILABILITY: http://compbio.med.harvard.edu/CGHweb.

Promoter profiling and coexpression data analysis identifies 24 novel genes that are coregulated with AMPA receptor genes, GRIAs.

We identified a set of transcriptional elements that are conserved and overrepresented within the promoters of human, mouse, and rat GRIAs by comparing these promoters against a collection of 10,741 gene promoters. Cells regulate functional groups of genes by coordinating the transcriptional and/or posttranscriptional mRNA levels of interacting genes. As such, it is expected that functional groups of genes share the same transcriptional features within their promoters. We found 47 genes whose promoters contain the same combination of transcriptional elements that are overrepresented within the promoters of the GRIA gene family. Coexpressed genes may be transcriptionally coregulated, which in turn suggests that these genes may play complementary roles within a particular functional context. Using microarray expression data, we found 24 (of the 47) genes that share not only a similar promoter profile with GRIAs but also a well-correlated gene expression profile and, thus, we believe these to be coregulated with GRIAs.

Dragon TF Association Miner: a system for exploring transcription factor associations through text-mining.

We present Dragon TF Association Miner (DTFAM), a system for text-mining of PubMed documents for potential functional association of transcription factors (TFs) with terms from Gene Ontology (GO) and with diseases. DTFAM has been trained and tested in the selection of relevant documents on a manually curated dataset containing >3000 PubMed abstracts relevant to transcription control. On our test data the system achieves sensitivity of 80% with specificity of 82%. DTFAM provides comprehensive tabular and graphical reports linking terms to relevant sets of documents. These documents are color-coded for easier inspection. DTFAM complements the existing biological resources by collecting, assessing, extracting and presenting associations that can reveal some of the not so easily observable connections among the entities found which could explain the functions of TFs and help decipher parts of gene transcriptional regulatory networks. DTFAM summarizes information from a large volume of documents saving time and making analysis simpler for individual users. DTFAM is freely available for academic and non-profit users at http://research.i2r.a-star.edu.sg/DRAGON/TFAM/.

Content analysis of the core promoter region of human genes.

We analyzed an extended core promoter regions covering [-70,+60] segment relative to the transcription start site of human promoters contained in the Eukaryotic Promoter Database. The analysis was made by using the Match program ver. 1.9 with an optimized setting and the TRANSFAC Professional database ver. 7.2. This analysis revealed that the most common transcription factor binding site in the examined collection of core promoters appears to be initiator (characterized by GEN_INI), which is expected. The other less obvious sites found were Spz1, E2F-1, ZF5, and C/EBP. The 'cap' site was also in this most common group. Over-representation of these sites relative to the non-promoter background data ranged from 0.3167 to 32.1645. These sites were characterized by being present in more than 60% of promoter sequences. Interestingly, the TATA-box has been found in only 11.63% of all examined promoters. The study is complemented by separate analyses of promoter groups having different GC content. These additional analyses revealed that the most common promoter elements found also include AP-2, CdxA, Pax-2, SRY, STAT1 and STAT5A. It was also observed that a number of promoter elements show strong preference either for the GC-rich or the GC-poor core promoters.